system

Abstract

Provide a system. A power measurement unit connected to each power consumption device; a data storage means for periodically receiving power usage data from the power measurement means and storing the data; data analysis means for analyzing the power usage data stored in the data storage means and generating recommended settings for power reduction; a notification means for notifying a user terminal of the recommended settings; a control means for controlling the power supply of each of the power consumption devices based on an instruction from the user terminal; a notification means for notifying a user of a state controlled by the control means; A system including:

Description

[Technical Field]

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

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

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

[0004] In recent years, changes in the global situation, power generation shortages, and abnormal weather have led to increased household power consumption, causing electricity bills to soar, especially in summer and winter. Under these circumstances, there is a need for optimization of power consumption that reduces the economic burden on households and is environmentally friendly. However, conventional power saving methods require manual operation by the user, making efficient power management difficult. Furthermore, standby power consumption has not been sufficiently reduced, resulting in wasted power consumption. A new system is needed to solve these problems. [Means for solving the problem]

[0005] To address the above-mentioned challenges, the present invention provides a system including a power meter connected to each power-using device, a data storage unit that periodically receives and stores power usage data from the power meter, a data analysis unit that analyzes the power usage data stored in the data storage unit and generates recommended settings for power reduction, a notification unit that notifies a user terminal of the recommended settings, a control unit that controls the power supply of each power-using device based on instructions from the user terminal, and a notification unit that notifies the user of the status controlled by the control unit. This system efficiently reduces power consumption by conserving standby power and automating on / off control of each home appliance through smart plugs. Furthermore, a notification unit using the LINE API can provide users with real-time information and suggestions. This allows for both reduced household electricity bills and a more comfortable lifestyle.

[0006] "Power-using devices" refers to all power-consuming devices and home appliances used in the home, and is a general term for devices that consume power.

[0007] The term "power measurement means" refers to a sensor or measuring device that is connected to a power-using device and measures the power consumption of the device.

[0008] The "data storage means" refers to a database or storage device for storing the power usage data received from the power measurement means.

[0009] "Data analysis means" refers to software or algorithms for analyzing the power usage data stored in the data storage means and evaluating power consumption patterns and efficiency.

[0010] "Recommended settings" refers to specific on / off settings and schedules generated by data analysis means for the purpose of reducing power consumption.

[0011] "Notification means" refers to the means of communication used to inform users of recommended settings and current power usage, and specifically refers to smartphone apps and LINE APIs.

[0012] A "user terminal" refers to a device used by a user, such as a smartphone, tablet, or PC, that receives notifications from the system and issues instructions.

[0013] The "control means" refers to a mechanism that turns the power of a power-using device on and off based on instructions from a user terminal or automated recommended settings, and specifically, a smart plug.

[0014] "LINE API" is an interface for sending and receiving messages programmatically through the LINE app, and is used as a means of notification. [Brief explanation of the drawings]

[0015] [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

[0016] 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.

[0017] First, the terms used in the following description will be explained.

[0018] 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).

[0019] 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.

[0020] 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.

[0021] 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.

[0022] 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."

[0023] [First embodiment]

[0024] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0025] 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.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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.

[0031] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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."

[0036] This invention is a smart plug AI system that connects to power-using devices in each home to reduce expensive electricity bills and realize a comfortable life. This system effectively manages energy consumption and automatically controls on / off, reducing standby power consumption.

[0037] Background and Overview

[0038] As part of home automation, the smart plug AI system is designed to allow users to easily monitor and control power usage through a smartphone or tablet app. The three parties involved - the server, the device, and the user - work together to achieve efficient power management.

[0039] System Configuration

[0040] 1. Power measurement means: A smart plug is connected to each power-using device and periodically measures its power consumption.

[0041] 2. Data storage means: The server receives the power usage data sent from the smart plug and stores it in a database.

[0042] 3. Data analysis means: The server analyzes the collected data and identifies power consumption patterns and wasted standby power.

[0043] 4. Recommended settings generation: Based on the results of the data analysis, the server generates on / off settings to reduce power consumption.

[0044] 5. Notification method: The server notifies the user device of recommended settings and current power usage status via the LINE API.

[0045] 6. Control means: The user terminal controls the on / off of the smart plug based on the received recommended settings.

[0046] Program processing overview

[0047] User Authentication

[0048] The server verifies the authentication information entered by the user in the app. When the user enters their ID and password, the information is sent to the server and checked against the database. If the correct information is provided, the user is allowed to access the system.

[0049] Collecting and storing electricity usage data

[0050] The smart plug periodically collects power consumption data from each connected power-using device and sends the data to a server, which stores the data in a database.

[0051] Analyzing data and generating recommendations

[0052] The server periodically analyzes the stored power usage data. Based on the analysis results, it identifies unnecessary standby power consumption and then generates recommendations for reducing it. These recommendations may include scheduling devices to be turned off during certain times of the day or recommending that devices be manually turned off to reduce standby power consumption.

[0053] Notification and User Approval

[0054] The generated recommended settings are sent to the user's device via the LINE API. After receiving the notification, the user can choose whether or not to accept the recommended settings. If accepted, a control command is sent to the smart plug.

[0055] Control and Status Notification

[0056] If the user device approves the recommended settings, the server sends a control command to the smart plug to turn off the power to the target power-using device. The user is again notified of the power-off status via the LINE API.

[0057] Specific examples

[0058] Example 1: Proposal for reducing standby power consumption at night

[0059] 1. The server analyzes power consumption data collected overnight and identifies home appliances (e.g., televisions) that consume a lot of standby power.

[0060] 2. Based on the analysis results, the server generates a recommendation to "turn off the TV at night to reduce standby power consumption."

[0061] 3. The settings will be notified to the user via the LINE API.

[0062] 4. If the user approves the recommended settings, the device sends an off command to the smart plug.

[0063] 5. The user will be notified via LINE that the TV has been turned off.

[0064] In this way, the smart plug AI system enables efficient management of power consumption, contributing to reducing household electricity bills and providing a comfortable living environment.

[0065] The processing flow will be explained below.

[0066] Step 1:

[0067] The user launches the smartphone app, enters their ID and password on the login screen, and presses the login button.

[0068] Step 2:

[0069] The device sends the user's input information (ID and password) to the server. Specifically, the app calls the server's authentication API and sends the ID and password.

[0070] Step 3:

[0071] The server checks the received ID and password against the user information in the database. The server searches for the user information and, if the data is correct, the authentication is successful.

[0072] Step 4:

[0073] The server returns the authentication result to the terminal. If the authentication is successful, the user proceeds to the next screen, and if the authentication is unsuccessful, an error message is displayed.

[0074] Step 5:

[0075] The smart plug periodically measures the power consumption of the connected power-using device, and the power measurement data is collected at regular intervals.

[0076] Step 6:

[0077] The smart plug sends the measured power consumption data to the server, which uses a specific data transmission protocol.

[0078] Step 7:

[0079] The server stores the received power consumption data in a database, along with a timestamp and device ID.

[0080] Step 8:

[0081] The server analyzes the power consumption data stored in the database. Data analysis algorithms analyze the power consumption patterns of each power-using device and identify wasted standby power.

[0082] Step 9:

[0083] Based on the analysis, the server generates recommendations for power saving, such as turning off the TV at night.

[0084] Step 10:

[0085] The server notifies the user device of the generated recommended settings using the LINE API, and the user receives a notification of the recommended settings on their smartphone.

[0086] Step 11:

[0087] The user checks the LINE notification and either approves or rejects the recommended settings. If they approve, the user presses the approve button through the app.

[0088] Step 12:

[0089] The device sends the user's approval to the server, which then controls the smart plug based on the approved recommended settings.

[0090] Step 13:

[0091] The server sends a control command to the smart plug, for example, "Turn off the TV."

[0092] Step 14:

[0093] The smart plug receives the control command to power off the connected power-using device, and sends a signal back to the server to confirm that the power has been turned off.

[0094] Step 15:

[0095] The server notifies the user device of the control result, and the user is notified via LINE that the power-using device has been turned off.

[0096] Through this series of processes, the smart plug AI system provides an environment where users can easily manage their power usage and save energy efficiently.

[0097] Example 1

[0098] 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."

[0099] The present invention relates to a technology for effectively managing energy consumption in the home and reducing unnecessary standby energy consumption, thereby saving on expensive electricity bills and realizing a comfortable living environment. However, conventional technologies have the problem of cumbersome management, since users must manually monitor and control each energy-using device. Furthermore, there is an insufficient mechanism for effectively analyzing energy consumption data and generating appropriate recommended settings, which limits the effectiveness of reducing standby energy consumption.

[0100] 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.

[0101] In this invention, the server includes energy measurement means connected to each energy usage device, data storage means for periodically receiving energy usage data from the energy measurement means and storing the data, data analysis means for analyzing the energy usage data stored in the data storage means and generating recommended settings for energy reduction, communication means for notifying a user terminal of the recommended settings, control means for controlling the power supply of each energy usage device based on instructions from the user terminal, and notification means for reporting the status of control by the control means to the user. This makes it possible to automatically and effectively manage energy consumption in the home, thereby reducing the user's effort and saving on expensive electricity bills.

[0102] An "energy measuring means" is a device that is connected to each energy-using device and that periodically measures energy consumption.

[0103] "Data storage means" means a device or system for storing energy usage data received from energy metering means.

[0104] The "data analysis means" is a device or system for analyzing the energy usage data stored in the data storage means and identifying energy consumption patterns and wasted standby energy.

[0105] The "recommended setting generating means" is a device or system for generating recommended settings for energy reduction based on the results of the data analyzing means.

[0106] "Communication means" refers to a device or system for notifying a user terminal of recommended settings and energy usage status.

[0107] The "control means" is a device or system for controlling the power supply of each energy usage device based on instructions from a user terminal.

[0108] The "notification means" is a device or system for reporting the state controlled by the control means to the user.

[0109] "User Device" means a device that allows a User to monitor energy usage and review, approve, or reject recommended settings.

[0110] This invention is a smart plug AI system that connects to energy-using devices in each home to reduce expensive electricity bills and realize a comfortable life. This system effectively manages energy consumption and automatically controls on / off, enabling standby energy reduction.

[0111] System Configuration

[0112] To implement this invention, the following components are required:

[0113] 1. Energy measurement method: Using smart plugs that are connected to each energy-using device and periodically measure power consumption.

[0114] 2. Data storage means: The server receives the power usage data transmitted from the smart plug and stores it in a database (e.g., MySQL (registered trademark), PostgreSQL).

[0115] 3. Data analysis: The server analyzes the collected data to identify energy consumption patterns and wasted standby energy. Data analysis software such as Python or R can be used for data analysis.

[0116] 4. Recommended setting generation method: The server generates on / off settings for energy saving based on the results of data analysis.

[0117] 5. Communication method: The server notifies the user's smartphone or tablet of recommended settings and current energy usage status via an external API such as the LINE API.

[0118] 6. Control: The user's smartphone or tablet controls the smart plug to turn on and off based on the recommended settings received.

[0119] 7. Notification means: The state controlled by the control means is reported to the user via the LINE API.

[0120] Specific examples

[0121] Example 1: Proposal for reducing standby energy consumption at night

[0122] 1. The server analyzes energy consumption data collected overnight and identifies appliances (e.g., televisions) that consume high standby energy.

[0123] 2. Based on the analysis results, the server generates a recommendation to "turn off the TV at night to reduce standby energy consumption."

[0124] 3. Recommended settings will be sent to the user's smartphone via the LINE API.

[0125] 4. Once the user accepts the recommended settings, their smartphone will send an off command to the smart plug.

[0126] 5. The user will be notified via LINE that the TV has been turned off.

[0127] Example prompts to input to the generative AI model

[0128] "Please explain how the smart plug AI system will recommend settings to reduce expensive electricity bills and how it will analyze specific energy consumption data. Please also provide details on how the system will notify users of the recommended settings and the control process that will be implemented after the notification is approved."

[0129] In this way, the present invention realizes efficient management of energy consumption, contributes to reducing household electricity bills, and provides a comfortable living environment.

[0130] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0131] Step 1: User authentication

[0132] The server receives the ID and password entered by the user in the app. For example, let's say the user enters "user123" and "password456".

[0133] Input: User ID and password

[0134] The server checks the received authentication information against the database, specifically to see if the user ID and password match.

[0135] Data processing: User ID and password verification

[0136] Output: Authentication result (success or failure)

[0137] The server returns a success response to the user if authentication is successful, or an error message if authentication is unsuccessful.

[0138] Step 2: Collecting electricity usage data

[0139] The smart plug periodically measures the power consumption of connected appliances (e.g., TV, air conditioner). For example, the TV's power consumption is measured as 150W and the air conditioner's power consumption is measured as 500W.

[0140] Input: Power consumption data for home appliances

[0141] The smart plug sends the measurement results to a server.

[0142] Data processing: Collecting and transmitting power consumption data

[0143] Output: Power consumption data sent to the server

[0144] Step 3: Save your energy usage data

[0145] The server stores the power usage data received from the smart plug in a database. For example, data such as "TV: 150W, Air Conditioner: 500W" is stored for the timestamp "2023-10-01 18:00:00."

[0146] Input: Power consumption data from smart plugs

[0147] Data processing: Saving to database

[0148] Output: Power consumption data stored in a database

[0149] Step 4: Data analysis

[0150] The server periodically analyzes the power usage data stored in the database, for example, identifying high standby power consumption at night based on data from the past week.

[0151] Input: Power usage data stored in the database

[0152] Data processing: Analysis of energy consumption patterns

[0153] Output: Standby energy identification results

[0154] Step 5: Generate recommendations

[0155] Based on the analysis results, the server generates recommended settings to reduce unnecessary energy consumption, such as "turn off the TV between 11:00 PM and 6:00 AM."

[0156] Input: Results of data analysis

[0157] Data Processing: Generating Recommendations

[0158] Output: Recommended settings

[0159] Step 6: Notification of recommended settings

[0160] The server then uses the LINE API to notify the user of the recommended settings on their smartphone, for example, sending a message such as "We recommend turning off the TV at 11:00 PM to reduce standby energy consumption at night."

[0161] Input: Generated recommended settings

[0162] Data processing: Notification content generation

[0163] Output: Notification via LINE API

[0164] Step 7: User Authorization

[0165] The user checks the LINE notification and either approves or rejects the recommended settings. For example, if the user selects "Approve," the approval information is sent to the server.

[0166] Input: LINE notification content

[0167] Data Processing: Accept or Reject

[0168] Output: Approval result

[0169] Step 8: Control your smart plug

[0170] The server, with the user's approval, sends a control command to the smart plug, for example, to turn off the TV at 11:00 PM.

[0171] Input: User approval result

[0172] Data processing: Generation and transmission of control commands

[0173] Output: Control command to the smart plug

[0174] Step 9: Notification of control results

[0175] The server receives the results of the control command from the smart plug and notifies the user via the LINE API. For example, it sends a notification to the user's smartphone saying, "The TV has been successfully turned off."

[0176] Input: Execution result from smart plug

[0177] Data processing: Notification content generation

[0178] Output: Notification via LINE API

[0179] (Application example 1)

[0180] 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."

[0181] There is a lack of means to optimize and efficiently manage power consumption in autonomous vehicles. There is also a need for a system that can quickly and accurately recommend appropriate power usage to drivers and manage it appropriately.

[0182] 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.

[0183] In this invention, the server includes a power metering means connected to each power consumption device, a data storage means for periodically receiving power consumption data from the power metering means and storing the data, a data analysis means for analyzing the power consumption data stored in the data storage means and generating recommended settings for power reduction, a notification means for notifying a user terminal of the recommended settings, a control means for controlling the power supply of each power consumption device based on an instruction from the user terminal, a notification means for notifying a user of a state controlled by the control means, a means for collecting and analyzing power consumption data of each power device in an autonomously driving vehicle, a means for generating recommended settings for optimizing power consumption of the vehicle based on the collected data, a means for notifying an infotainment system of the vehicle of the recommended settings, a means for controlling each power consumption device based on an instruction from the infotainment system, and a means for obtaining approval from the driver to control the device, thereby enabling optimization and efficient management of power consumption in an autonomously driving vehicle.

[0184] A "power measurement means" is a means that is connected to a power-using device and that periodically measures the power consumption of that device.

[0185] The "data storage means" is a means for storing the power usage data received from the power measurement means.

[0186] The "data analysis means" is a means for analyzing the power usage data stored in the data storage means and generating recommended settings for reducing power consumption.

[0187] The "notification means" is a means for notifying the generated recommended settings to the user terminal.

[0188] The "control means" is a means for controlling the power supply of each power consumption device based on instructions from a user terminal.

[0189] An "autonomous vehicle" is a vehicle that can drive autonomously without the need for human operation.

[0190] "Power device" refers to any device in a vehicle that consumes power.

[0191] An "infotainment system" is a system that provides information and entertainment functions within a vehicle.

[0192] The "recommended setting generating means" is a means for generating recommended settings for optimizing power usage based on collected data.

[0193] The "driver approval means" is a means for obtaining approval from the driver for the recommended settings for controlling the power devices.

[0194] This invention is a system for optimizing and efficiently managing power consumption in an autonomous vehicle. This system is composed of a power measurement means, a data storage means, a data analysis means, a notification means, and a control means. The system also works in conjunction with the vehicle's infotainment system to notify the driver of recommended settings for optimized power consumption and automatically control the power supply of devices as needed.

[0195] Hardware and software used

[0196] In-vehicle sensors: Attached to each power device and used to measure power consumption.

[0197] Infotainment system: Used to notify and control the driver.

[0198] Communication module: Handles data communication between the vehicle and the cloud server.

[0199] Cloud data server: (Amazon Web Services, Google® Cloud, etc.) Analyzes data and generates recommended settings.

[0200] LINE API: Used to send notifications to drivers.

[0201] Program processing overview

[0202] In this system, first, the power measurement means periodically measures the power consumption of each power device and collects data. The data is transmitted to a cloud data server via a communication module and stored in a data storage means. Next, the data analysis means analyzes the data and generates recommended settings to optimize the vehicle's power consumption.

[0203] The generated recommended settings are notified to the driver via notification means. Notification methods include a message notification using the LINE API or a notification on the infotainment system screen. The driver can choose to accept or reject the recommendation, and if accepted, the control means will carry out the appropriate control for each power device. The control status of the power devices is also fed back to the driver via the notification means.

[0204] Specific examples

[0205] Power management during long-distance driving

[0206] System operation flow

[0207] 1. Periodically collect power consumption data from the vehicle's air conditioning and audio systems.

[0208] 2. The collected data is sent to a cloud server in real time and stored in a data storage means.

[0209] 3. The data analysis means analyzes the data and generates recommended settings (e.g., reducing the volume of the audio system, adjusting the air conditioning temperature) to achieve efficient power management during long-distance driving.

[0210] 4. The recommended settings will be notified to the driver via the LINE API or the infotainment system screen.

[0211] 5. If the driver approves the recommended settings, the control means sends control commands to the relevant devices to optimize power usage.

[0212] Prompt Sentence Examples

[0213] "For the next section of the journey, would you like your air conditioning system to lower the temperature by 2 degrees to reduce power consumption? (Yes / No)"

[0214] "Optimizing the volume of your audio system can reduce power consumption. Apply settings? (Yes / No)"

[0215] In this way, the present invention allows for efficient management of power consumption within an autonomous vehicle, optimizing overall power usage and improving operational efficiency.

[0216] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0217] Step 1:

[0218] The power measurement means periodically measures the power consumption of each power device (for example, an air conditioning system or an audio system) and collects the data. This process calculates the power using voltage and current information obtained from the attached sensors and records this as time-series data. The input is voltage and current data, and the output is the power consumption data of each device.

[0219] Step 2:

[0220] The data storage means periodically receives collected power consumption data and transmits it to the cloud server, which stores the received data in a database. The input is the power consumption data from the smart plugs and sensors, and the output is the power consumption records stored in the cloud database.

[0221] Step 3:

[0222] The data analysis means analyzes the power consumption data stored in the database. This includes statistical processing to determine hourly consumption patterns and detect anomalies. Specifically, it uses data mining techniques to identify areas of unnecessary power consumption. The input is the stored power consumption data, and the output is power consumption patterns and recommended optimization settings.

[0223] Step 4:

[0224] The recommended settings generation means generates recommended settings to optimize power consumption based on the analysis results. For example, a setting such as "lower the air conditioning temperature by 2 degrees to reduce power consumption during long-distance driving" is generated. The input is the data analysis results, and the output is the specific recommended settings.

[0225] Step 5:

[0226] The notification means notifies the driver of the generated recommended settings via the LINE API or the infotainment system. The notification content includes an overview of the recommended settings and a message requesting approval. The input is the recommended settings, and the output is a notification to the driver. Specific actions include sending a prompt message via LINE.

[0227] Step 6:

[0228] The user receives a notification and can approve or reject the recommended settings. This approval operation is performed on the infotainment system screen or via LINE message. The input is the notification message, and the output is the response of approval or rejection.

[0229] Step 7:

[0230] The control means controls each power device based on the approved recommended settings, for example, lowering the temperature of the air conditioner or adjusting the volume of the audio system. The input is approval from the user, and the output is a control command to the device.

[0231] Step 8:

[0232] The result of the control performed by the control means is again notified to the driver via the notification means. This notification includes feedback on whether the setting change was successful. The input is the control result, and the output is the feedback notification to the driver.

[0233] This allows power consumption within autonomous vehicles to be optimized and efficiently managed.

[0234] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0235] This invention combines a smart plug AI system connected to power-using devices in each home with an emotion engine that recognizes the user's emotions, aiming to reduce expensive electricity bills and realize a comfortable lifestyle. This system effectively manages energy consumption and automatically controls on and off, thereby reducing standby power consumption. The emotion engine also recognizes the user's emotional state and provides optimal notifications and control.

[0236] Background and Overview

[0237] Increasing household energy consumption not only puts a strain on household finances but also impacts the environment. To address this issue, the smart plug AI system monitors and manages energy usage via an app on the user's smartphone or tablet, enabling optimal energy consumption. Furthermore, a newly integrated emotion engine recognizes the user's emotional state in real time and provides appropriate notifications accordingly.

[0238] System Configuration

[0239] Power measurement means

[0240] A smart plug is connected to each power-using device and periodically measures its power consumption.

[0241] Data Storage Means

[0242] The server receives the power usage data sent by the smart plug and stores it in a database.

[0243] Data Analysis Methods

[0244] The server analyzes the collected data to identify power consumption patterns and wasted standby power.

[0245] Recommendation Generation

[0246] Based on the results of the data analysis, the server generates recommended settings for reducing power consumption, such as turning off the TV at night.

[0247] Notification means

[0248] The server notifies the user's device of recommended settings and current power usage status via the LINE API.

[0249] Control means

[0250] The user terminal controls the on / off of the smart plug based on the received recommended settings.

[0251] Emotion Engine

[0252] The emotion engine uses sensors such as the camera and microphone installed on the user's smartphone to recognize the user's emotional state (e.g., joy, anger, sadness, surprise, etc.) in real time.

[0253] Program processing overview

[0254] User Authentication

[0255] The server verifies the authentication information entered by the user in the app. When the user enters their ID and password, the information is sent to the server and checked against the database. If the correct information is provided, the user is allowed to access the system.

[0256] Collecting and storing electricity usage data

[0257] The smart plug periodically collects power consumption data from each connected power-using device and sends the data to a server, which stores the data in a database.

[0258] Analyzing data and generating recommendations

[0259] The server periodically analyzes the stored power usage data. Based on the analysis results, it identifies unnecessary standby power consumption and then generates recommendations for reducing it. These recommendations may include scheduling devices to be turned off during certain times of the day or recommending that devices be manually turned off to reduce standby power consumption.

[0260] Emotion Engine Operation

[0261] The emotion engine analyzes the user's emotional state and sends that information to the server. For example, if the user is feeling stressed, the notification message will be adjusted to something more gentle.

[0262] Notification and User Approval

[0263] The generated recommended settings are sent to the user's device via the LINE API. After receiving the notification, the user can choose whether or not to accept the recommended settings. If accepted, a control command is sent to the smart plug.

[0264] Control and Status Notification

[0265] Once the user device approves the recommended settings, the server sends a control command to the smart plug to turn off the power to the target power-using device. The user is again notified of the power-off state via the LINE API.

[0266] Specific examples

[0267] Example 1: Reducing standby power consumption at night and responding to emotional states

[0268] 1. The server analyzes the power consumption data collected overnight and identifies home appliances (e.g., televisions) that consume a lot of standby power.

[0269] 2. Based on the analysis results, the server generates a recommendation to "turn off the TV at night to reduce standby power consumption."

[0270] 3. The emotion engine analyzes the user's emotional state in real time, and if the user is relaxed, for example, the notification content will be changed to a calmer tone.

[0271] 4. Once the user approves the recommended settings notified via the LINE API, the device will send an off command to the smart plug.

[0272] 5. The user will be notified again via LINE notification that the TV has been turned off.

[0273] In this way, the smart plug AI system of the present invention takes into account the user's emotions while efficiently managing and reducing power consumption, contributing to providing a comfortable living environment for users.

[0274] The processing flow will be explained below.

[0275] Step 1:

[0276] The user launches the smartphone app, enters their ID and password on the login screen, and presses the login button.

[0277] Step 2:

[0278] The device sends the user's input information (ID and password) to the server. Specifically, the app calls the server's authentication API and sends the ID and password.

[0279] Step 3:

[0280] The server checks the received ID and password against the user information in the database. The server searches for the user information and, if the data is correct, the authentication is successful.

[0281] Step 4:

[0282] The server returns the authentication result to the terminal. If the authentication is successful, the user proceeds to the next screen, and if the authentication is unsuccessful, an error message is displayed.

[0283] Step 5:

[0284] The smart plug periodically measures the power consumption of the connected power-using device, and the power measurement data is collected at regular intervals.

[0285] Step 6:

[0286] The smart plug sends the measured power consumption data to the server, which uses a specific data transmission protocol.

[0287] Step 7:

[0288] The server stores the received power consumption data in a database, along with a timestamp and device ID.

[0289] Step 8:

[0290] The server analyzes the power consumption data stored in the database. Data analysis algorithms analyze the power consumption patterns of each power-using device and identify wasted standby power.

[0291] Step 9:

[0292] The emotion engine analyzes the user's emotional state. It uses sensors such as the camera and microphone on the user's smartphone to collect emotional data and analyze it in real time.

[0293] Step 10:

[0294] The emotion engine analyzes the emotion data and sends it to the server, providing a basis for tailoring the content of notifications based on the user's emotional state.

[0295] Step 11:

[0296] Based on the analysis, the server generates recommendations for power saving, such as turning off the TV at night.

[0297] Step 12:

[0298] The server notifies the user device of the generated recommended settings, for example, using the LINE API to communicate the recommended settings to the user.

[0299] Step 13:

[0300] The content of notifications is adjusted based on data from the emotion engine. For example, if the user is feeling stressed, the notification content will be changed to a more calming message.

[0301] Step 14:

[0302] The user checks the LINE notification and presses the approve button through the app if they approve the recommended settings. If they reject the settings, they press the reject button.

[0303] Step 15:

[0304] The terminal sends the user's approval or denial to the server, and the server performs the following process depending on the information received:

[0305] Step 16:

[0306] The server sends a control command to the smart plug, for example, "Turn off the TV."

[0307] Step 17:

[0308] The smart plug receives the control command to power off the connected power-using device, and sends a signal back to the server to confirm that the power has been turned off.

[0309] Step 18:

[0310] The server notifies the user device of the control result, and the user is notified via LINE that the power-using device has been turned off.

[0311] Through this series of processes, the smart plug AI system provides an environment where users can easily manage their power usage and efficiently save energy.In addition, the emotion engine provides notifications that take into account the user's emotional state, providing a more personalized experience.

[0312] Example 2

[0313] 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."

[0314] Conventional power management systems have difficulty effectively reducing the standby power consumption of individual power-using devices, resulting in continued wasted power consumption. Furthermore, they lack the ability to respond flexibly to the user's emotional state, limiting the improvement of the user experience.

[0315] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a power measurement means connected to each power consuming device, a data storage means, a data analysis means, a notification means, a control means, a notification means, an emotion engine, and a notification adjustment means. This enables efficient management of power consumption and appropriate notification according to the user's emotional state.

[0316] The "power measurement means" is a device that is connected to each power consuming device and periodically measures the power consumption of that device.

[0317] The "data storage means" is a device or function for storing the power usage data received from the power measurement means.

[0318] The "data analysis means" is a device or function that analyzes the power usage data stored in the data storage means and generates recommended settings for reducing power consumption.

[0319] The "notification means" is a device or function for transmitting recommended settings and power usage information to a user terminal.

[0320] The "control means" is a device or function that controls the power supply of each power consumption device based on instructions from a user terminal.

[0321] An "emotion engine" is a device or function that identifies a user's emotional state in real time and transmits that information to a server.

[0322] The "notification adjustment means" is a device or function that adjusts the notification content based on the emotional state obtained by the emotion engine.

[0323] The "message sending API" is an application programming interface that allows a notification means to send a notification to a user terminal.

[0324] This invention combines a smart plug AI system connected to power-using devices in each home with an emotion engine that recognizes the user's emotions. The goal is to reduce wasteful energy consumption, save on expensive electricity bills, and realize a comfortable lifestyle. This system effectively manages energy consumption and automatically controls on and off, thereby reducing standby power consumption. The emotion engine also recognizes the user's emotional state and provides optimal notifications and control.

[0325] System Configuration

[0326] Power measurement means

[0327] A smart plug connected to each power-using device periodically measures power consumption. For example, a smart plug is connected to each power-using device in a home (refrigerator, TV, air conditioner, etc.).

[0328] Data Storage Means

[0329] The server receives the power usage data sent by the smart plugs and stores it in a database, which includes information such as the power consumption, usage time, and standby power consumption of each device.

[0330] Data Analysis Methods

[0331] The server periodically analyzes the power usage data stored in the database and uses data mining techniques to identify power consumption patterns and generate configuration recommendations to reduce unnecessary standby power consumption.

[0332] Recommendation Generation

[0333] Based on the results of the data analysis, the server generates specific recommendations for power reduction, such as turning off the TV at night or manually turning off unused devices.

[0334] Notification means

[0335] The server notifies the user device of the generated recommended settings and the current power usage status using a message sending API, allowing the user to receive power usage optimization information in real time.

[0336] Control means

[0337] The user device controls the smart plug's on / off state based on the received recommended settings, for example, sending a command to turn off a specific device at night.

[0338] Emotion Engine

[0339] The emotion engine uses sensors such as the camera and microphone on the user's smartphone to recognize the user's emotional state in real time. For example, if the user is feeling stressed, the engine changes the wording of the notification message to something more calming.

[0340] Specific examples

[0341] Example 1: Reducing standby power consumption at night and responding to emotional states

[0342] 1. The server analyzes the power consumption data collected overnight and identifies home appliances (e.g., televisions) that consume a lot of standby power.

[0343] 2. Based on the analysis results, the server generates a recommendation to "turn off the TV at night to reduce standby power consumption."

[0344] 3. The emotion engine analyzes the user's emotional state in real time, and if the user is relaxed, for example, the notification content will be changed to a calmer tone.

[0345] 4. If the user approves the recommended settings, the device sends an off command to the smart plug.

[0346] 5. A notification will again inform the user that the TV has been turned off.

[0347] Examples of prompt statements

[0348] Analyze the power usage of your next device, identify unnecessary standby power consumption, and generate optimal notifications based on the user's emotional state.

[0349] Thus, the system of the present invention has a multi-functional configuration and realizes efficient management and reduction of power consumption while taking into account the emotional state of the user.

[0350] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0351] Step 1:

[0352] (user authentication)

[0353] Specific actions

[0354] Input: The ID and password entered by the user into the app.

[0355] Processing: The server receives the authentication information sent by the user and checks it against the information stored in the database.

[0356] Output: If authentication is successful, an authentication token is issued.

[0357] Operation: If the authentication is successful, the server issues an authentication token to the user and sends it to the user's terminal.

[0358] Step 2:

[0359] (Collection and storage of electricity usage data)

[0360] Specific actions

[0361] Input: Power consumption data that the smart plug periodically obtains from each power-using device.

[0362] Processing: The smart plug collects the data and sends it to the server, which stores it in a database.

[0363] Output: Power usage data stored in a database.

[0364] How it works: The smart plug periodically collects power consumption data from each power-using device and sends it to a server, which stores the data in a database.

[0365] Step 3:

[0366] (Data analysis and generation of recommendations)

[0367] Specific actions

[0368] Input: Power usage data stored in a database.

[0369] Processing: The server uses data mining techniques to analyze power usage patterns, identify unnecessary standby power consumption, and generate power reduction recommendations.

[0370] Output: The generated recommendations.

[0371] How it works: The server analyzes power usage data stored in a database to identify unnecessary standby power consumption, then generates specific recommendations for reducing power consumption.

[0372] Step 4:

[0373] (Emotion engine in action)

[0374] Specific actions

[0375] Input: Emotion data obtained from the user's smartphone (via camera and microphone).

[0376] Processing: The emotion engine analyzes the user's emotional state in real time and sends the information to the server.

[0377] Output: Data about emotional state.

[0378] How it works: The emotion engine collects emotion data from the user's smartphone, analyzes it in real time, and sends the results to the server.

[0379] Step 5:

[0380] (Notification and User Approval)

[0381] Specific actions

[0382] Input: Generated recommendation settings, user emotional state data.

[0383] Processing: The server sends the recommended settings to the user as a notification. The notification content is adjusted based on the emotion data. The user receives the notification and can choose whether to accept the recommended settings.

[0384] Output: User approval or disapproval.

[0385] How it works: The server uses the LINE API or similar to send a notification to the user based on the generated recommended settings and emotion data. The user receives the notification and can choose whether to accept or reject it. If they accept, the information is sent to the server.

[0386] Step 6:

[0387] (control and status notification)

[0388] Specific actions

[0389] Input: Control commands based on user authorization.

[0390] Processing: The server receives the authorization information and sends a control command to the smart plug, which turns off the power of the target device.

[0391] Output: Device powered off state.

[0392] Operation: With the user's approval, the server sends a control command to the smart plug. The smart plug turns off the power to the target power-using device based on the command. It notifies the user again via the LINE API that the device is powered off.

[0393] (Application example 2)

[0394] 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."

[0395] While conventional home energy management systems have focused on reducing and efficiently managing energy consumption, they were unable to provide personalized notifications or suggestions that took into account the user's emotional state. Furthermore, there was a need for a system that could provide a more comfortable and efficient living environment by combining the control of energy-using devices with the user's purchasing experience.

[0396] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes power measurement means connected to each power consumption device, data storage means for periodically receiving power consumption data from the power measurement means and storing the data, data analysis means for analyzing the power consumption data stored in the data storage means and generating recommended settings for power reduction, notification means for notifying a user terminal of the recommended settings, control means for controlling the power supply of each power consumption device based on instructions from the user terminal, notification means for notifying the user of the state controlled by the control means, an emotion engine for analyzing the user's emotions and making optimal product suggestions and notifications based on the analysis results, and recommended setting adjustment means for adjusting the content of the recommended settings based on information from the emotion engine. This makes it possible to efficiently manage power consumption while also providing personalized suggestions and notifications based on the user's emotions.

[0397] The "power measurement means" is a device that is connected to each power consumption device and periodically measures power consumption data.

[0398] The "data storage means" is a device or system that stores the power usage data received from the power measurement means.

[0399] The "data analysis means" is a device or system that analyzes the power usage data stored in the data storage means and generates recommended settings for reducing power consumption.

[0400] The "notification means" is a device or system that notifies the user terminal of recommended settings, power usage status, and the like.

[0401] The "control means" is a device or system that controls the power supply of each power consumption device based on instructions from a user terminal.

[0402] An "emotion engine" is a system or algorithm that analyzes users' emotions and makes optimal product suggestions and notifications based on the analysis results.

[0403] The "recommended settings adjustment means" is a device or system that adjusts the content of recommended settings based on information from the emotion engine.

[0404] This invention combines a smart plug AI system connected to power-using devices in each home with an emotion engine that recognizes the user's emotions. The goal is to reduce expensive electricity bills and realize a comfortable lifestyle. This system effectively manages energy consumption and automatically controls on / off, thereby reducing standby power consumption. The emotion engine also recognizes the user's emotional state and provides optimal notifications and product suggestions accordingly.

[0405] System Configuration

[0406] Power measurement means

[0407] A smart plug is connected to each power-using device and periodically measures its power consumption, sending the measured data to a server.

[0408] Data Storage Means

[0409] The server receives the power usage data sent by the smart plug and stores it in a database for later analysis.

[0410] Data Analysis Methods

[0411] The server analyzes the collected data to identify power consumption patterns and wasted standby power, and generates recommendations for reducing power consumption.

[0412] Notification means

[0413] The server notifies the user device of recommended settings and current power usage status via a common message sending API such as the LINE API.

[0414] Control means

[0415] The user terminal controls the smart plug to turn on and off based on the received recommended settings, and the change in power supply status is reported to the user again via the notification means.

[0416] Emotion Engine

[0417] The emotion engine uses sensors such as the camera and microphone installed on the user's smartphone to recognize the user's emotional state (e.g., joy, anger, sadness, surprise, etc.) in real time. The recognized emotions are sent to the server.

[0418] Recommended settings adjustments

[0419] Based on the user's emotional state provided by the emotion engine, the server adjusts the recommended settings, for example, changing the notification wording to something more gentle if the user is feeling stressed.

[0420] Data processing and calculation

[0421] The program is primarily implemented using Python.

[0422] Facial Recognition and Emotion Analysis: Using OpenCV and emotion recognition models (Keras and TENSORFLOW®), we capture the user's face and analyze their emotions.

[0423] Data analysis: Use Pandas and NumPy to analyze the electricity usage data stored in the database.

[0424] Notification system: Notify users using LINE API or other common messaging APIs.

[0425] Specific examples

[0426] Example 1: Reducing standby power consumption at night and responding to emotional states

[0427] 1. The server analyzes the power consumption data collected overnight and identifies home appliances (e.g., televisions) that consume a lot of standby power.

[0428] 2. Based on the analysis results, the server generates a recommendation to "turn off the TV at night to reduce standby power consumption."

[0429] 3. The emotion engine analyzes the user's emotional state in real time, and if the user is relaxed, for example, the notification content will be changed to a calmer tone.

[0430] 4. Once the user approves the recommended settings notified via the LINE API, the device will send an off command to the smart plug.

[0431] 5. The user will be notified again via LINE notification that the TV has been turned off.

[0432] Example prompts to input to the generative AI model

[0433] Generate appropriate product suggestions based on user emotions, for example, suggest popular products when the user is happy, or relaxation products when the user is stressed.

[0434] In this way, the smart plug AI system of the present invention takes into account the user's emotions while efficiently managing and reducing power consumption, contributing to providing a comfortable living environment for users.

[0435] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0436] Step 1:

[0437] The server receives periodic power usage data from the smart plug and stores the data in a database. The smart plug is connected to each power-using device and measures power consumption. The measured power usage data is sent to the server and stored in the database for later analysis. The input is the power usage data from the smart plug, and the output is the data stored in the database.

[0438] Step 2:

[0439] The server analyzes the power usage data stored in the database. Specifically, it uses Python libraries such as Pandas and NumPy to identify power consumption patterns and wasteful standby power. The input is the power usage data stored in the database, and the output is recommended settings for power reduction.

[0440] Step 3:

[0441] The server uses a general messaging API such as the LINE API to notify the user device of the generated recommended settings. The input is the recommended settings generated in step 2, and the output is the notification sent to the user device.

[0442] Step 4:

[0443] The emotion engine uses sensors such as the camera and microphone on the user's smartphone to recognize the user's emotional state in real time. For example, it uses OpenCV and an emotion recognition model to analyze emotions from the user's face. The input is sensor data from the smartphone's camera and microphone, and the output is the emotion analysis result.

[0444] Step 5:

[0445] The server adjusts the recommended settings based on the emotional state provided by the emotion engine. For example, if the user is feeling stressed, the notification wording is changed to a more gentle one. The input is the emotion analysis result from the emotion engine, and the output is the adjusted recommended settings.

[0446] Step 6:

[0447] The user terminal controls the on / off of the smart plug based on the received recommended settings after adjustment. The input is the recommended settings after adjustment sent from the server, and the output is the control command for the smart plug.

[0448] Step 7:

[0449] The server then reports the smart plug's control results to the user again using a notification method. For example, it may notify the user via the LINE API that the smart plug has turned off the power-using device. The input is the smart plug's control result, and the output is a notification sent to the user's device.

[0450] 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.

[0451] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0452] 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.

[0453] [Second embodiment]

[0454] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0455] 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.

[0456] 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).

[0457] 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.

[0458] 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.

[0459] 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).

[0460] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0461] 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.

[0462] 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.

[0463] 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.

[0464] 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.

[0465] 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."

[0466] This invention is a smart plug AI system that connects to power-using devices in each home to reduce expensive electricity bills and realize a comfortable life. This system effectively manages energy consumption and automatically controls on / off, reducing standby power consumption.

[0467] Background and Overview

[0468] As part of home automation, the smart plug AI system is designed to allow users to easily monitor and control power usage through a smartphone or tablet app. The three parties involved - the server, the device, and the user - work together to achieve efficient power management.

[0469] System Configuration

[0470] 1. Power measurement means: A smart plug is connected to each power-using device and periodically measures its power consumption.

[0471] 2. Data storage means: The server receives the power usage data sent from the smart plug and stores it in a database.

[0472] 3. Data analysis means: The server analyzes the collected data and identifies power consumption patterns and wasted standby power.

[0473] 4. Recommended settings generation: Based on the results of the data analysis, the server generates on / off settings to reduce power consumption.

[0474] 5. Notification method: The server notifies the user device of recommended settings and current power usage status via the LINE API.

[0475] 6. Control means: The user terminal controls the on / off of the smart plug based on the received recommended settings.

[0476] Program processing overview

[0477] User Authentication

[0478] The server verifies the authentication information entered by the user in the app. When the user enters their ID and password, the information is sent to the server and checked against the database. If the correct information is provided, the user is allowed to access the system.

[0479] Collecting and storing electricity usage data

[0480] The smart plug periodically collects power consumption data from each connected power-using device and sends the data to a server, which stores the data in a database.

[0481] Analyzing data and generating recommendations

[0482] The server periodically analyzes the stored power usage data. Based on the analysis results, it identifies unnecessary standby power consumption and then generates recommendations for reducing it. These recommendations may include scheduling devices to be turned off during certain times of the day or recommending that devices be manually turned off to reduce standby power consumption.

[0483] Notification and User Approval

[0484] The generated recommended settings are sent to the user's device via the LINE API. After receiving the notification, the user can choose whether or not to accept the recommended settings. If accepted, a control command is sent to the smart plug.

[0485] Control and Status Notification

[0486] If the user device approves the recommended settings, the server sends a control command to the smart plug to turn off the power to the target power-using device. The user is again notified of the power-off status via the LINE API.

[0487] Specific examples

[0488] Example 1: Proposal for reducing standby power consumption at night

[0489] 1. The server analyzes power consumption data collected overnight and identifies home appliances (e.g., televisions) that consume a lot of standby power.

[0490] 2. Based on the analysis results, the server generates a recommendation to "turn off the TV at night to reduce standby power consumption."

[0491] 3. The settings will be notified to the user via the LINE API.

[0492] 4. If the user approves the recommended settings, the device sends an off command to the smart plug.

[0493] 5. The user will be notified via LINE that the TV has been turned off.

[0494] In this way, the smart plug AI system enables efficient management of power consumption, contributing to reducing household electricity bills and providing a comfortable living environment.

[0495] The processing flow will be explained below.

[0496] Step 1:

[0497] The user launches the smartphone app, enters their ID and password on the login screen, and presses the login button.

[0498] Step 2:

[0499] The device sends the user's input information (ID and password) to the server. Specifically, the app calls the server's authentication API and sends the ID and password.

[0500] Step 3:

[0501] The server checks the received ID and password against the user information in the database. The server searches for the user information and, if the data is correct, the authentication is successful.

[0502] Step 4:

[0503] The server returns the authentication result to the terminal. If the authentication is successful, the user proceeds to the next screen, and if the authentication is unsuccessful, an error message is displayed.

[0504] Step 5:

[0505] The smart plug periodically measures the power consumption of the connected power-using device, and the power measurement data is collected at regular intervals.

[0506] Step 6:

[0507] The smart plug sends the measured power consumption data to the server, which uses a specific data transmission protocol.

[0508] Step 7:

[0509] The server stores the received power consumption data in a database, along with a timestamp and device ID.

[0510] Step 8:

[0511] The server analyzes the power consumption data stored in the database. Data analysis algorithms analyze the power consumption patterns of each power-using device and identify wasted standby power.

[0512] Step 9:

[0513] Based on the analysis, the server generates recommendations for power saving, such as turning off the TV at night.

[0514] Step 10:

[0515] The server notifies the user device of the generated recommended settings using the LINE API, and the user receives a notification of the recommended settings on their smartphone.

[0516] Step 11:

[0517] The user checks the LINE notification and either approves or rejects the recommended settings. If they approve, the user presses the approve button through the app.

[0518] Step 12:

[0519] The device sends the user's approval to the server, which then controls the smart plug based on the approved recommended settings.

[0520] Step 13:

[0521] The server sends a control command to the smart plug, for example, "Turn off the TV."

[0522] Step 14:

[0523] The smart plug receives the control command to power off the connected power-using device, and sends a signal back to the server to confirm that the power has been turned off.

[0524] Step 15:

[0525] The server notifies the user device of the control result, and the user is notified via LINE that the power-using device has been turned off.

[0526] Through this series of processes, the smart plug AI system provides an environment where users can easily manage their power usage and save energy efficiently.

[0527] Example 1

[0528] 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."

[0529] The present invention relates to a technology for effectively managing energy consumption in the home and reducing unnecessary standby energy consumption, thereby saving on expensive electricity bills and realizing a comfortable living environment. However, conventional technologies have the problem of cumbersome management, since users must manually monitor and control each energy-using device. Furthermore, there is an insufficient mechanism for effectively analyzing energy consumption data and generating appropriate recommended settings, which limits the effectiveness of reducing standby energy consumption.

[0530] 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.

[0531] In this invention, the server includes energy measurement means connected to each energy usage device, data storage means for periodically receiving energy usage data from the energy measurement means and storing the data, data analysis means for analyzing the energy usage data stored in the data storage means and generating recommended settings for energy reduction, communication means for notifying a user terminal of the recommended settings, control means for controlling the power supply of each energy usage device based on instructions from the user terminal, and notification means for reporting the status of control by the control means to the user. This makes it possible to automatically and effectively manage energy consumption in the home, thereby reducing the user's effort and saving on expensive electricity bills.

[0532] An "energy measuring means" is a device that is connected to each energy-using device and that periodically measures energy consumption.

[0533] "Data storage means" means a device or system for storing energy usage data received from energy metering means.

[0534] The "data analysis means" is a device or system for analyzing the energy usage data stored in the data storage means and identifying energy consumption patterns and wasted standby energy.

[0535] The "recommended setting generating means" is a device or system for generating recommended settings for energy reduction based on the results of the data analyzing means.

[0536] "Communication means" refers to a device or system for notifying a user terminal of recommended settings and energy usage status.

[0537] The "control means" is a device or system for controlling the power supply of each energy usage device based on instructions from a user terminal.

[0538] The "notification means" is a device or system for reporting the state controlled by the control means to the user.

[0539] "User Device" means a device that allows a User to monitor energy usage and review, approve, or reject recommended settings.

[0540] This invention is a smart plug AI system that connects to energy-using devices in each home to reduce expensive electricity bills and realize a comfortable life. This system effectively manages energy consumption and automatically controls on / off, enabling standby energy reduction.

[0541] System Configuration

[0542] To implement this invention, the following components are required:

[0543] 1. Energy measurement method: Using smart plugs that are connected to each energy-using device and periodically measure power consumption.

[0544] 2. Data storage means: The server receives the power usage data sent from the smart plug and stores it in a database (e.g., MySQL, PostgreSQL).

[0545] 3. Data analysis: The server analyzes the collected data to identify energy consumption patterns and wasted standby energy. Data analysis software such as Python or R can be used for data analysis.

[0546] 4. Recommended setting generation method: The server generates on / off settings for energy saving based on the results of data analysis.

[0547] 5. Communication method: The server notifies the user's smartphone or tablet of recommended settings and current energy usage status via an external API such as the LINE API.

[0548] 6. Control: The user's smartphone or tablet controls the smart plug to turn on and off based on the recommended settings received.

[0549] 7. Notification means: The state controlled by the control means is reported to the user via the LINE API.

[0550] Specific examples

[0551] Example 1: Proposal for reducing standby energy consumption at night

[0552] 1. The server analyzes energy consumption data collected overnight and identifies appliances (e.g., televisions) that consume high standby energy.

[0553] 2. Based on the analysis results, the server generates a recommendation to "turn off the TV at night to reduce standby energy consumption."

[0554] 3. Recommended settings will be sent to the user's smartphone via the LINE API.

[0555] 4. Once the user accepts the recommended settings, their smartphone will send an off command to the smart plug.

[0556] 5. The user will be notified via LINE that the TV has been turned off.

[0557] Example prompts to input to the generative AI model

[0558] "Please explain how the smart plug AI system will recommend settings to reduce expensive electricity bills and how it will analyze specific energy consumption data. Please also provide details on how the system will notify users of the recommended settings and the control process that will be implemented after the notification is approved."

[0559] In this way, the present invention realizes efficient management of energy consumption, contributes to reducing household electricity bills, and provides a comfortable living environment.

[0560] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0561] Step 1: User authentication

[0562] The server receives the ID and password entered by the user in the app. For example, let's say the user enters "user123" and "password456".

[0563] Input: User ID and password

[0564] The server checks the received authentication information against the database, specifically to see if the user ID and password match.

[0565] Data processing: User ID and password verification

[0566] Output: Authentication result (success or failure)

[0567] The server returns a success response to the user if authentication is successful, or an error message if authentication is unsuccessful.

[0568] Step 2: Collecting electricity usage data

[0569] The smart plug periodically measures the power consumption of connected appliances (e.g., TV, air conditioner). For example, the TV's power consumption is measured as 150W and the air conditioner's power consumption is measured as 500W.

[0570] Input: Power consumption data for home appliances

[0571] The smart plug sends the measurement results to a server.

[0572] Data processing: Collecting and transmitting power consumption data

[0573] Output: Power consumption data sent to the server

[0574] Step 3: Save your energy usage data

[0575] The server stores the power usage data received from the smart plug in a database. For example, data such as "TV: 150W, Air Conditioner: 500W" is stored for the timestamp "2023-10-01 18:00:00."

[0576] Input: Power consumption data from smart plugs

[0577] Data processing: Saving to database

[0578] Output: Power consumption data stored in a database

[0579] Step 4: Data analysis

[0580] The server periodically analyzes the power usage data stored in the database, for example, identifying high standby power consumption at night based on data from the past week.

[0581] Input: Power usage data stored in the database

[0582] Data processing: Analysis of energy consumption patterns

[0583] Output: Standby energy identification results

[0584] Step 5: Generate recommendations

[0585] Based on the analysis results, the server generates recommended settings to reduce unnecessary energy consumption, such as "turn off the TV between 11:00 PM and 6:00 AM."

[0586] Input: Results of data analysis

[0587] Data Processing: Generating Recommendations

[0588] Output: Recommended settings

[0589] Step 6: Notification of recommended settings

[0590] The server then uses the LINE API to notify the user of the recommended settings on their smartphone, for example, sending a message such as "We recommend turning off the TV at 11:00 PM to reduce standby energy consumption at night."

[0591] Input: Generated recommended settings

[0592] Data processing: Notification content generation

[0593] Output: Notification via LINE API

[0594] Step 7: User Authorization

[0595] The user checks the LINE notification and either approves or rejects the recommended settings. For example, if the user selects "Approve," the approval information is sent to the server.

[0596] Input: LINE notification content

[0597] Data Processing: Accept or Reject

[0598] Output: Approval result

[0599] Step 8: Control your smart plug

[0600] The server, with the user's approval, sends a control command to the smart plug, for example, to turn off the TV at 11:00 PM.

[0601] Input: User approval result

[0602] Data processing: Generation and transmission of control commands

[0603] Output: Control command to the smart plug

[0604] Step 9: Notification of control results

[0605] The server receives the results of the control command from the smart plug and notifies the user via the LINE API. For example, it sends a notification to the user's smartphone saying, "The TV has been successfully turned off."

[0606] Input: Execution result from smart plug

[0607] Data processing: Notification content generation

[0608] Output: Notification via LINE API

[0609] (Application example 1)

[0610] 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."

[0611] There is a lack of means to optimize and efficiently manage power consumption in autonomous vehicles. There is also a need for a system that can quickly and accurately recommend appropriate power usage to drivers and manage it appropriately.

[0612] 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.

[0613] In this invention, the server includes a power metering means connected to each power consumption device, a data storage means for periodically receiving power consumption data from the power metering means and storing the data, a data analysis means for analyzing the power consumption data stored in the data storage means and generating recommended settings for power reduction, a notification means for notifying a user terminal of the recommended settings, a control means for controlling the power supply of each power consumption device based on an instruction from the user terminal, a notification means for notifying a user of a state controlled by the control means, a means for collecting and analyzing power consumption data of each power device in an autonomously driving vehicle, a means for generating recommended settings for optimizing power consumption of the vehicle based on the collected data, a means for notifying an infotainment system of the vehicle of the recommended settings, a means for controlling each power consumption device based on an instruction from the infotainment system, and a means for obtaining approval from the driver to control the device, thereby enabling optimization and efficient management of power consumption in an autonomously driving vehicle.

[0614] A "power measurement means" is a means that is connected to a power-using device and that periodically measures the power consumption of that device.

[0615] The "data storage means" is a means for storing the power usage data received from the power measurement means.

[0616] The "data analysis means" is a means for analyzing the power usage data stored in the data storage means and generating recommended settings for reducing power consumption.

[0617] The "notification means" is a means for notifying the generated recommended settings to the user terminal.

[0618] The "control means" is a means for controlling the power supply of each power consumption device based on instructions from a user terminal.

[0619] An "autonomous vehicle" is a vehicle that can drive autonomously without the need for human operation.

[0620] "Power device" refers to any device in a vehicle that consumes power.

[0621] An "infotainment system" is a system that provides information and entertainment functions within a vehicle.

[0622] The "recommended setting generating means" is a means for generating recommended settings for optimizing power usage based on collected data.

[0623] The "driver approval means" is a means for obtaining approval from the driver for the recommended settings for controlling the power devices.

[0624] This invention is a system for optimizing and efficiently managing power consumption in an autonomous vehicle. This system is composed of a power measurement means, a data storage means, a data analysis means, a notification means, and a control means. The system also works in conjunction with the vehicle's infotainment system to notify the driver of recommended settings for optimized power consumption and automatically control the power supply of devices as needed.

[0625] Hardware and software used

[0626] In-vehicle sensors: Attached to each power device and used to measure power consumption.

[0627] Infotainment system: Used to notify and control the driver.

[0628] Communication module: Handles data communication between the vehicle and the cloud server.

[0629] Cloud data servers (Amazon Web Services, Google Cloud, etc.) analyze data and generate recommended configurations.

[0630] LINE API: Used to send notifications to drivers.

[0631] Program processing overview

[0632] In this system, first, the power measurement means periodically measures the power consumption of each power device and collects data. The data is transmitted to a cloud data server via a communication module and stored in a data storage means. Next, the data analysis means analyzes the data and generates recommended settings to optimize the vehicle's power consumption.

[0633] The generated recommended settings are notified to the driver via notification means. Notification methods include a message notification using the LINE API or a notification on the infotainment system screen. The driver can choose to accept or reject the recommendation, and if accepted, the control means will carry out the appropriate control for each power device. The control status of the power devices is also fed back to the driver via the notification means.

[0634] Specific examples

[0635] Power management during long-distance driving

[0636] System operation flow

[0637] 1. Periodically collect power consumption data from the vehicle's air conditioning and audio systems.

[0638] 2. The collected data is sent to a cloud server in real time and stored in a data storage means.

[0639] 3. The data analysis means analyzes the data and generates recommended settings (e.g., reducing the volume of the audio system, adjusting the air conditioning temperature) to achieve efficient power management during long-distance driving.

[0640] 4. The recommended settings will be notified to the driver via the LINE API or the infotainment system screen.

[0641] 5. If the driver approves the recommended settings, the control means sends control commands to the relevant devices to optimize power usage.

[0642] Prompt Sentence Examples

[0643] "For the next section of the journey, would you like your air conditioning system to lower the temperature by 2 degrees to reduce power consumption? (Yes / No)"

[0644] "Optimizing the volume of your audio system can reduce power consumption. Apply settings? (Yes / No)"

[0645] In this way, the present invention allows for efficient management of power consumption within an autonomous vehicle, optimizing overall power usage and improving operational efficiency.

[0646] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0647] Step 1:

[0648] The power measurement means periodically measures the power consumption of each power device (for example, an air conditioning system or an audio system) and collects the data. This process calculates the power using voltage and current information obtained from the attached sensors and records this as time-series data. The input is voltage and current data, and the output is the power consumption data of each device.

[0649] Step 2:

[0650] The data storage means periodically receives collected power consumption data and transmits it to the cloud server, which stores the received data in a database. The input is the power consumption data from the smart plugs and sensors, and the output is the power consumption records stored in the cloud database.

[0651] Step 3:

[0652] The data analysis means analyzes the power consumption data stored in the database. This includes statistical processing to determine hourly consumption patterns and detect anomalies. Specifically, it uses data mining techniques to identify areas of unnecessary power consumption. The input is the stored power consumption data, and the output is power consumption patterns and recommended optimization settings.

[0653] Step 4:

[0654] The recommended settings generation means generates recommended settings to optimize power consumption based on the analysis results. For example, a setting such as "lower the air conditioning temperature by 2 degrees to reduce power consumption during long-distance driving" is generated. The input is the data analysis results, and the output is the specific recommended settings.

[0655] Step 5:

[0656] The notification means notifies the driver of the generated recommended settings via the LINE API or the infotainment system. The notification content includes an overview of the recommended settings and a message requesting approval. The input is the recommended settings, and the output is a notification to the driver. Specific actions include sending a prompt message via LINE.

[0657] Step 6:

[0658] The user receives a notification and can approve or reject the recommended settings. This approval operation is performed on the infotainment system screen or via LINE message. The input is the notification message, and the output is the response of approval or rejection.

[0659] Step 7:

[0660] The control means controls each power device based on the approved recommended settings, for example, lowering the temperature of the air conditioner or adjusting the volume of the audio system. The input is approval from the user, and the output is a control command to the device.

[0661] Step 8:

[0662] The result of the control performed by the control means is again notified to the driver via the notification means. This notification includes feedback on whether the setting change was successful. The input is the control result, and the output is the feedback notification to the driver.

[0663] This allows power consumption within autonomous vehicles to be optimized and efficiently managed.

[0664] 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.

[0665] This invention combines a smart plug AI system connected to power-using devices in each home with an emotion engine that recognizes the user's emotions, aiming to reduce expensive electricity bills and realize a comfortable lifestyle. This system effectively manages energy consumption and automatically controls on and off, thereby reducing standby power consumption. The emotion engine also recognizes the user's emotional state and provides optimal notifications and control.

[0666] Background and Overview

[0667] Increasing household energy consumption not only puts a strain on household finances but also impacts the environment. To address this issue, the smart plug AI system monitors and manages energy usage via an app on the user's smartphone or tablet, enabling optimal energy consumption. Furthermore, a newly integrated emotion engine recognizes the user's emotional state in real time and provides appropriate notifications accordingly.

[0668] System Configuration

[0669] Power measurement means

[0670] A smart plug is connected to each power-using device and periodically measures its power consumption.

[0671] Data Storage Means

[0672] The server receives the power usage data sent by the smart plug and stores it in a database.

[0673] Data Analysis Methods

[0674] The server analyzes the collected data to identify power consumption patterns and wasted standby power.

[0675] Recommendation Generation

[0676] Based on the results of the data analysis, the server generates recommended settings for reducing power consumption, such as turning off the TV at night.

[0677] Notification means

[0678] The server notifies the user's device of recommended settings and current power usage status via the LINE API.

[0679] Control means

[0680] The user terminal controls the on / off of the smart plug based on the received recommended settings.

[0681] Emotion Engine

[0682] The emotion engine uses sensors such as the camera and microphone installed on the user's smartphone to recognize the user's emotional state (e.g., joy, anger, sadness, surprise, etc.) in real time.

[0683] Program processing overview

[0684] User Authentication

[0685] The server verifies the authentication information entered by the user in the app. When the user enters their ID and password, the information is sent to the server and checked against the database. If the correct information is provided, the user is allowed to access the system.

[0686] Collecting and storing electricity usage data

[0687] The smart plug periodically collects power consumption data from each connected power-using device and sends the data to a server, which stores the data in a database.

[0688] Analyzing data and generating recommendations

[0689] The server periodically analyzes the stored power usage data. Based on the analysis results, it identifies unnecessary standby power consumption and then generates recommendations for reducing it. These recommendations may include scheduling devices to be turned off during certain times of the day or recommending that devices be manually turned off to reduce standby power consumption.

[0690] Emotion Engine Operation

[0691] The emotion engine analyzes the user's emotional state and sends that information to the server. For example, if the user is feeling stressed, the notification message will be adjusted to something more gentle.

[0692] Notification and User Approval

[0693] The generated recommended settings are sent to the user's device via the LINE API. After receiving the notification, the user can choose whether or not to accept the recommended settings. If accepted, a control command is sent to the smart plug.

[0694] Control and Status Notification

[0695] Once the user device approves the recommended settings, the server sends a control command to the smart plug to turn off the power to the target power-using device. The user is again notified of the power-off state via the LINE API.

[0696] Specific examples

[0697] Example 1: Reducing standby power consumption at night and responding to emotional states

[0698] 1. The server analyzes the power consumption data collected overnight and identifies home appliances (e.g., televisions) that consume a lot of standby power.

[0699] 2. Based on the analysis results, the server generates a recommendation to "turn off the TV at night to reduce standby power consumption."

[0700] 3. The emotion engine analyzes the user's emotional state in real time, and if the user is relaxed, for example, the notification content will be changed to a calmer tone.

[0701] 4. Once the user approves the recommended settings notified via the LINE API, the device will send an off command to the smart plug.

[0702] 5. The user will be notified again via LINE notification that the TV has been turned off.

[0703] In this way, the smart plug AI system of the present invention takes into account the user's emotions while efficiently managing and reducing power consumption, contributing to providing a comfortable living environment for users.

[0704] The processing flow will be explained below.

[0705] Step 1:

[0706] The user launches the smartphone app, enters their ID and password on the login screen, and presses the login button.

[0707] Step 2:

[0708] The device sends the user's input information (ID and password) to the server. Specifically, the app calls the server's authentication API and sends the ID and password.

[0709] Step 3:

[0710] The server checks the received ID and password against the user information in the database. The server searches for the user information and, if the data is correct, the authentication is successful.

[0711] Step 4:

[0712] The server returns the authentication result to the terminal. If the authentication is successful, the user proceeds to the next screen, and if the authentication is unsuccessful, an error message is displayed.

[0713] Step 5:

[0714] The smart plug periodically measures the power consumption of the connected power-using device, and the power measurement data is collected at regular intervals.

[0715] Step 6:

[0716] The smart plug sends the measured power consumption data to the server, which uses a specific data transmission protocol.

[0717] Step 7:

[0718] The server stores the received power consumption data in a database, along with a timestamp and device ID.

[0719] Step 8:

[0720] The server analyzes the power consumption data stored in the database. Data analysis algorithms analyze the power consumption patterns of each power-using device and identify wasted standby power.

[0721] Step 9:

[0722] The emotion engine analyzes the user's emotional state. It uses sensors such as the camera and microphone on the user's smartphone to collect emotional data and analyze it in real time.

[0723] Step 10:

[0724] The emotion engine analyzes the emotion data and sends it to the server, providing a basis for tailoring the content of notifications based on the user's emotional state.

[0725] Step 11:

[0726] Based on the analysis, the server generates recommendations for power saving, such as turning off the TV at night.

[0727] Step 12:

[0728] The server notifies the user device of the generated recommended settings, for example, using the LINE API to communicate the recommended settings to the user.

[0729] Step 13:

[0730] The content of notifications is adjusted based on data from the emotion engine. For example, if the user is feeling stressed, the notification content will be changed to a more calming message.

[0731] Step 14:

[0732] The user checks the LINE notification and presses the approve button through the app if they approve the recommended settings. If they reject the settings, they press the reject button.

[0733] Step 15:

[0734] The terminal sends the user's approval or denial to the server, and the server performs the following process depending on the information received:

[0735] Step 16:

[0736] The server sends a control command to the smart plug, for example, "Turn off the TV."

[0737] Step 17:

[0738] The smart plug receives the control command to power off the connected power-using device, and sends a signal back to the server to confirm that the power has been turned off.

[0739] Step 18:

[0740] The server notifies the user device of the control result, and the user is notified via LINE that the power-using device has been turned off.

[0741] Through this series of processes, the smart plug AI system provides an environment where users can easily manage their power usage and efficiently save energy.In addition, the emotion engine provides notifications that take into account the user's emotional state, providing a more personalized experience.

[0742] Example 2

[0743] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0744] Conventional power management systems have difficulty effectively reducing the standby power consumption of individual power-using devices, resulting in continued wasted power consumption. Furthermore, they lack the ability to respond flexibly to the user's emotional state, limiting the improvement of the user experience.

[0745] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a power measurement means connected to each power consuming device, a data storage means, a data analysis means, a notification means, a control means, a notification means, an emotion engine, and a notification adjustment means. This enables efficient management of power consumption and appropriate notification according to the user's emotional state.

[0746] The "power measurement means" is a device that is connected to each power consuming device and periodically measures the power consumption of that device.

[0747] The "data storage means" is a device or function for storing the power usage data received from the power measurement means.

[0748] The "data analysis means" is a device or function that analyzes the power usage data stored in the data storage means and generates recommended settings for reducing power consumption.

[0749] The "notification means" is a device or function for transmitting recommended settings and power usage information to a user terminal.

[0750] The "control means" is a device or function that controls the power supply of each power consumption device based on instructions from a user terminal.

[0751] An "emotion engine" is a device or function that identifies a user's emotional state in real time and transmits that information to a server.

[0752] The "notification adjustment means" is a device or function that adjusts the notification content based on the emotional state obtained by the emotion engine.

[0753] The "message sending API" is an application programming interface that allows a notification means to send a notification to a user terminal.

[0754] This invention combines a smart plug AI system connected to power-using devices in each home with an emotion engine that recognizes the user's emotions. The goal is to reduce wasteful energy consumption, save on expensive electricity bills, and realize a comfortable lifestyle. This system effectively manages energy consumption and automatically controls on and off, thereby reducing standby power consumption. The emotion engine also recognizes the user's emotional state and provides optimal notifications and control.

[0755] System Configuration

[0756] Power measurement means

[0757] A smart plug connected to each power-using device periodically measures power consumption. For example, a smart plug is connected to each power-using device in a home (refrigerator, TV, air conditioner, etc.).

[0758] Data Storage Means

[0759] The server receives the power usage data sent by the smart plugs and stores it in a database, which includes information such as the power consumption, usage time, and standby power consumption of each device.

[0760] Data Analysis Methods

[0761] The server periodically analyzes the power usage data stored in the database and uses data mining techniques to identify power consumption patterns and generate configuration recommendations to reduce unnecessary standby power consumption.

[0762] Recommendation Generation

[0763] Based on the results of the data analysis, the server generates specific recommendations for power reduction, such as turning off the TV at night or manually turning off unused devices.

[0764] Notification means

[0765] The server notifies the user device of the generated recommended settings and the current power usage status using a message sending API, allowing the user to receive power usage optimization information in real time.

[0766] Control means

[0767] The user device controls the smart plug's on / off state based on the received recommended settings, for example, sending a command to turn off a specific device at night.

[0768] Emotion Engine

[0769] The emotion engine uses sensors such as the camera and microphone on the user's smartphone to recognize the user's emotional state in real time. For example, if the user is feeling stressed, the engine changes the wording of the notification message to something more calming.

[0770] Specific examples

[0771] Example 1: Reducing standby power consumption at night and responding to emotional states

[0772] 1. The server analyzes the power consumption data collected overnight and identifies home appliances (e.g., televisions) that consume a lot of standby power.

[0773] 2. Based on the analysis results, the server generates a recommendation to "turn off the TV at night to reduce standby power consumption."

[0774] 3. The emotion engine analyzes the user's emotional state in real time, and if the user is relaxed, for example, the notification content will be changed to a calmer tone.

[0775] 4. If the user approves the recommended settings, the device sends an off command to the smart plug.

[0776] 5. A notification will again inform the user that the TV has been turned off.

[0777] Examples of prompt statements

[0778] Analyze the power usage of your next device, identify unnecessary standby power consumption, and generate optimal notifications based on the user's emotional state.

[0779] Thus, the system of the present invention has a multi-functional configuration and realizes efficient management and reduction of power consumption while taking into account the emotional state of the user.

[0780] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0781] Step 1:

[0782] (user authentication)

[0783] Specific actions

[0784] Input: The ID and password entered by the user into the app.

[0785] Processing: The server receives the authentication information sent by the user and checks it against the information stored in the database.

[0786] Output: If authentication is successful, an authentication token is issued.

[0787] Operation: If the authentication is successful, the server issues an authentication token to the user and sends it to the user's terminal.

[0788] Step 2:

[0789] (Collection and storage of electricity usage data)

[0790] Specific actions

[0791] Input: Power consumption data that the smart plug periodically obtains from each power-using device.

[0792] Processing: The smart plug collects the data and sends it to the server, which stores it in a database.

[0793] Output: Power usage data stored in a database.

[0794] How it works: The smart plug periodically collects power consumption data from each power-using device and sends it to a server, which stores the data in a database.

[0795] Step 3:

[0796] (Data analysis and generation of recommendations)

[0797] Specific actions

[0798] Input: Power usage data stored in a database.

[0799] Processing: The server uses data mining techniques to analyze power usage patterns, identify unnecessary standby power consumption, and generate power reduction recommendations.

[0800] Output: The generated recommendations.

[0801] How it works: The server analyzes power usage data stored in a database to identify unnecessary standby power consumption, then generates specific recommendations for reducing power consumption.

[0802] Step 4:

[0803] (Emotion engine in action)

[0804] Specific actions

[0805] Input: Emotion data obtained from the user's smartphone (via camera and microphone).

[0806] Processing: The emotion engine analyzes the user's emotional state in real time and sends the information to the server.

[0807] Output: Data about emotional state.

[0808] How it works: The emotion engine collects emotion data from the user's smartphone, analyzes it in real time, and sends the results to the server.

[0809] Step 5:

[0810] (Notification and User Approval)

[0811] Specific actions

[0812] Input: Generated recommendation settings, user emotional state data.

[0813] Processing: The server sends the recommended settings to the user as a notification. The notification content is adjusted based on the emotion data. The user receives the notification and can choose whether to accept the recommended settings.

[0814] Output: User approval or disapproval.

[0815] How it works: The server uses the LINE API or similar to send a notification to the user based on the generated recommended settings and emotion data. The user receives the notification and can choose whether to accept or reject it. If they accept, the information is sent to the server.

[0816] Step 6:

[0817] (control and status notification)

[0818] Specific actions

[0819] Input: Control commands based on user authorization.

[0820] Processing: The server receives the authorization information and sends a control command to the smart plug, which turns off the power of the target device.

[0821] Output: Device powered off state.

[0822] Operation: With the user's approval, the server sends a control command to the smart plug. The smart plug turns off the power to the target power-using device based on the command. It notifies the user again via the LINE API that the device is powered off.

[0823] (Application example 2)

[0824] 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."

[0825] While conventional home energy management systems have focused on reducing and efficiently managing energy consumption, they were unable to provide personalized notifications or suggestions that took into account the user's emotional state. Furthermore, there was a need for a system that could provide a more comfortable and efficient living environment by combining the control of energy-using devices with the user's purchasing experience.

[0826] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes power measurement means connected to each power consumption device, data storage means for periodically receiving power consumption data from the power measurement means and storing the data, data analysis means for analyzing the power consumption data stored in the data storage means and generating recommended settings for power reduction, notification means for notifying a user terminal of the recommended settings, control means for controlling the power supply of each power consumption device based on instructions from the user terminal, notification means for notifying the user of the state controlled by the control means, an emotion engine for analyzing the user's emotions and making optimal product suggestions and notifications based on the analysis results, and recommended setting adjustment means for adjusting the content of the recommended settings based on information from the emotion engine. This makes it possible to efficiently manage power consumption while also providing personalized suggestions and notifications based on the user's emotions.

[0827] The "power measurement means" is a device that is connected to each power consumption device and periodically measures power consumption data.

[0828] The "data storage means" is a device or system that stores the power usage data received from the power measurement means.

[0829] The "data analysis means" is a device or system that analyzes the power usage data stored in the data storage means and generates recommended settings for reducing power consumption.

[0830] The "notification means" is a device or system that notifies the user terminal of recommended settings, power usage status, and the like.

[0831] The "control means" is a device or system that controls the power supply of each power consumption device based on instructions from a user terminal.

[0832] An "emotion engine" is a system or algorithm that analyzes users' emotions and makes optimal product suggestions and notifications based on the analysis results.

[0833] The "recommended settings adjustment means" is a device or system that adjusts the content of recommended settings based on information from the emotion engine.

[0834] This invention combines a smart plug AI system connected to power-using devices in each home with an emotion engine that recognizes the user's emotions. The goal is to reduce expensive electricity bills and realize a comfortable lifestyle. This system effectively manages energy consumption and automatically controls on / off, thereby reducing standby power consumption. The emotion engine also recognizes the user's emotional state and provides optimal notifications and product suggestions accordingly.

[0835] System Configuration

[0836] Power measurement means

[0837] A smart plug is connected to each power-using device and periodically measures its power consumption, sending the measured data to a server.

[0838] Data Storage Means

[0839] The server receives the power usage data sent by the smart plug and stores it in a database for later analysis.

[0840] Data Analysis Methods

[0841] The server analyzes the collected data to identify power consumption patterns and wasted standby power, and generates recommendations for reducing power consumption.

[0842] Notification means

[0843] The server notifies the user device of recommended settings and current power usage status via a common message sending API such as the LINE API.

[0844] Control means

[0845] The user terminal controls the smart plug to turn on and off based on the received recommended settings, and the change in power supply status is reported to the user again via the notification means.

[0846] Emotion Engine

[0847] The emotion engine uses sensors such as the camera and microphone installed on the user's smartphone to recognize the user's emotional state (e.g., joy, anger, sadness, surprise, etc.) in real time. The recognized emotions are sent to the server.

[0848] Recommended settings adjustments

[0849] Based on the user's emotional state provided by the emotion engine, the server adjusts the recommended settings, for example, changing the notification wording to something more gentle if the user is feeling stressed.

[0850] Data processing and calculation

[0851] The program is primarily implemented using Python.

[0852] Facial Recognition and Emotion Analysis: Capture the user's face and analyze their emotions using OpenCV and emotion recognition models (Keras and TensorFlow).

[0853] Data analysis: Use Pandas and NumPy to analyze the electricity usage data stored in the database.

[0854] Notification system: Notify users using LINE API or other common messaging APIs.

[0855] Specific examples

[0856] Example 1: Reducing standby power consumption at night and responding to emotional states

[0857] 1. The server analyzes the power consumption data collected overnight and identifies home appliances (e.g., televisions) that consume a lot of standby power.

[0858] 2. Based on the analysis results, the server generates a recommendation to "turn off the TV at night to reduce standby power consumption."

[0859] 3. The emotion engine analyzes the user's emotional state in real time, and if the user is relaxed, for example, the notification content will be changed to a calmer tone.

[0860] 4. Once the user approves the recommended settings notified via the LINE API, the device will send an off command to the smart plug.

[0861] 5. The user will be notified again via LINE notification that the TV has been turned off.

[0862] Example prompts to input to the generative AI model

[0863] Generate appropriate product suggestions based on user emotions, for example, suggest popular products when the user is happy, or relaxation products when the user is stressed.

[0864] In this way, the smart plug AI system of the present invention takes into account the user's emotions while efficiently managing and reducing power consumption, contributing to providing a comfortable living environment for users.

[0865] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0866] Step 1:

[0867] The server receives periodic power usage data from the smart plug and stores the data in a database. The smart plug is connected to each power-using device and measures power consumption. The measured power usage data is sent to the server and stored in the database for later analysis. The input is the power usage data from the smart plug, and the output is the data stored in the database.

[0868] Step 2:

[0869] The server analyzes the power usage data stored in the database. Specifically, it uses Python libraries such as Pandas and NumPy to identify power consumption patterns and wasteful standby power. The input is the power usage data stored in the database, and the output is recommended settings for power reduction.

[0870] Step 3:

[0871] The server uses a general messaging API such as the LINE API to notify the user device of the generated recommended settings. The input is the recommended settings generated in step 2, and the output is the notification sent to the user device.

[0872] Step 4:

[0873] The emotion engine uses sensors such as the camera and microphone on the user's smartphone to recognize the user's emotional state in real time. For example, it uses OpenCV and an emotion recognition model to analyze emotions from the user's face. The input is sensor data from the smartphone's camera and microphone, and the output is the emotion analysis result.

[0874] Step 5:

[0875] The server adjusts the recommended settings based on the emotional state provided by the emotion engine. For example, if the user is feeling stressed, the notification wording is changed to a more gentle one. The input is the emotion analysis result from the emotion engine, and the output is the adjusted recommended settings.

[0876] Step 6:

[0877] The user terminal controls the on / off of the smart plug based on the received recommended settings after adjustment. The input is the recommended settings after adjustment sent from the server, and the output is the control command for the smart plug.

[0878] Step 7:

[0879] The server then reports the smart plug's control results to the user again using a notification method. For example, it may notify the user via the LINE API that the smart plug has turned off the power-using device. The input is the smart plug's control result, and the output is a notification sent to the user's device.

[0880] 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.

[0881] 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.

[0882] 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.

[0883] [Third embodiment]

[0884] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0885] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0886] 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).

[0887] 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.

[0888] 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.

[0889] 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).

[0890] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0891] 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.

[0892] 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.

[0893] 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.

[0894] 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.

[0895] 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."

[0896] This invention is a smart plug AI system that connects to power-using devices in each home to reduce expensive electricity bills and realize a comfortable life. This system effectively manages energy consumption and automatically controls on / off, reducing standby power consumption.

[0897] Background and Overview

[0898] As part of home automation, the smart plug AI system is designed to allow users to easily monitor and control power usage through a smartphone or tablet app. The three parties involved - the server, the device, and the user - work together to achieve efficient power management.

[0899] System Configuration

[0900] 1. Power measurement means: A smart plug is connected to each power-using device and periodically measures its power consumption.

[0901] 2. Data storage means: The server receives the power usage data sent from the smart plug and stores it in a database.

[0902] 3. Data analysis means: The server analyzes the collected data and identifies power consumption patterns and wasted standby power.

[0903] 4. Recommended settings generation: Based on the results of the data analysis, the server generates on / off settings to reduce power consumption.

[0904] 5. Notification method: The server notifies the user device of recommended settings and current power usage status via the LINE API.

[0905] 6. Control means: The user terminal controls the on / off of the smart plug based on the received recommended settings.

[0906] Program processing overview

[0907] User Authentication

[0908] The server verifies the authentication information entered by the user in the app. When the user enters their ID and password, the information is sent to the server and checked against the database. If the correct information is provided, the user is allowed to access the system.

[0909] Collecting and storing electricity usage data

[0910] The smart plug periodically collects power consumption data from each connected power-using device and sends the data to a server, which stores the data in a database.

[0911] Analyzing data and generating recommendations

[0912] The server periodically analyzes the stored power usage data. Based on the analysis results, it identifies unnecessary standby power consumption and then generates recommendations for reducing it. These recommendations may include scheduling devices to be turned off during certain times of the day or recommending that devices be manually turned off to reduce standby power consumption.

[0913] Notification and User Approval

[0914] The generated recommended settings are sent to the user's device via the LINE API. After receiving the notification, the user can choose whether or not to accept the recommended settings. If accepted, a control command is sent to the smart plug.

[0915] Control and Status Notification

[0916] If the user device approves the recommended settings, the server sends a control command to the smart plug to turn off the power to the target power-using device. The user is again notified of the power-off status via the LINE API.

[0917] Specific examples

[0918] Example 1: Proposal for reducing standby power consumption at night

[0919] 1. The server analyzes power consumption data collected overnight and identifies home appliances (e.g., televisions) that consume a lot of standby power.

[0920] 2. Based on the analysis results, the server generates a recommendation to "turn off the TV at night to reduce standby power consumption."

[0921] 3. The settings will be notified to the user via the LINE API.

[0922] 4. If the user approves the recommended settings, the device sends an off command to the smart plug.

[0923] 5. The user will be notified via LINE that the TV has been turned off.

[0924] In this way, the smart plug AI system enables efficient management of power consumption, contributing to reducing household electricity bills and providing a comfortable living environment.

[0925] The processing flow will be explained below.

[0926] Step 1:

[0927] The user launches the smartphone app, enters their ID and password on the login screen, and presses the login button.

[0928] Step 2:

[0929] The device sends the user's input information (ID and password) to the server. Specifically, the app calls the server's authentication API and sends the ID and password.

[0930] Step 3:

[0931] The server checks the received ID and password against the user information in the database. The server searches for the user information and, if the data is correct, the authentication is successful.

[0932] Step 4:

[0933] The server returns the authentication result to the terminal. If the authentication is successful, the user proceeds to the next screen, and if the authentication is unsuccessful, an error message is displayed.

[0934] Step 5:

[0935] The smart plug periodically measures the power consumption of the connected power-using device, and the power measurement data is collected at regular intervals.

[0936] Step 6:

[0937] The smart plug sends the measured power consumption data to the server, which uses a specific data transmission protocol.

[0938] Step 7:

[0939] The server stores the received power consumption data in a database, along with a timestamp and device ID.

[0940] Step 8:

[0941] The server analyzes the power consumption data stored in the database. Data analysis algorithms analyze the power consumption patterns of each power-using device and identify wasted standby power.

[0942] Step 9:

[0943] Based on the analysis, the server generates recommendations for power saving, such as turning off the TV at night.

[0944] Step 10:

[0945] The server notifies the user device of the generated recommended settings using the LINE API, and the user receives a notification of the recommended settings on their smartphone.

[0946] Step 11:

[0947] The user checks the LINE notification and either approves or rejects the recommended settings. If they approve, the user presses the approve button through the app.

[0948] Step 12:

[0949] The device sends the user's approval to the server, which then controls the smart plug based on the approved recommended settings.

[0950] Step 13:

[0951] The server sends a control command to the smart plug, for example, "Turn off the TV."

[0952] Step 14:

[0953] The smart plug receives the control command to power off the connected power-using device, and sends a signal back to the server to confirm that the power has been turned off.

[0954] Step 15:

[0955] The server notifies the user device of the control result, and the user is notified via LINE that the power-using device has been turned off.

[0956] Through this series of processes, the smart plug AI system provides an environment where users can easily manage their power usage and save energy efficiently.

[0957] Example 1

[0958] 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."

[0959] The present invention relates to a technology for effectively managing energy consumption in the home and reducing unnecessary standby energy consumption, thereby saving on expensive electricity bills and realizing a comfortable living environment. However, conventional technologies have the problem of cumbersome management, since users must manually monitor and control each energy-using device. Furthermore, there is an insufficient mechanism for effectively analyzing energy consumption data and generating appropriate recommended settings, which limits the effectiveness of reducing standby energy consumption.

[0960] 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.

[0961] In this invention, the server includes energy measurement means connected to each energy usage device, data storage means for periodically receiving energy usage data from the energy measurement means and storing the data, data analysis means for analyzing the energy usage data stored in the data storage means and generating recommended settings for energy reduction, communication means for notifying a user terminal of the recommended settings, control means for controlling the power supply of each energy usage device based on instructions from the user terminal, and notification means for reporting the status of control by the control means to the user. This makes it possible to automatically and effectively manage energy consumption in the home, thereby reducing the user's effort and saving on expensive electricity bills.

[0962] An "energy measuring means" is a device that is connected to each energy-using device and that periodically measures energy consumption.

[0963] "Data storage means" means a device or system for storing energy usage data received from energy metering means.

[0964] The "data analysis means" is a device or system for analyzing the energy usage data stored in the data storage means and identifying energy consumption patterns and wasted standby energy.

[0965] The "recommended setting generating means" is a device or system for generating recommended settings for energy reduction based on the results of the data analyzing means.

[0966] "Communication means" refers to a device or system for notifying a user terminal of recommended settings and energy usage status.

[0967] The "control means" is a device or system for controlling the power supply of each energy usage device based on instructions from a user terminal.

[0968] The "notification means" is a device or system for reporting the state controlled by the control means to the user.

[0969] "User Device" means a device that allows a User to monitor energy usage and review, approve, or reject recommended settings.

[0970] This invention is a smart plug AI system that connects to energy-using devices in each home to reduce expensive electricity bills and realize a comfortable life. This system effectively manages energy consumption and automatically controls on / off, enabling standby energy reduction.

[0971] System Configuration

[0972] To implement this invention, the following components are required:

[0973] 1. Energy measurement method: Using smart plugs that are connected to each energy-using device and periodically measure power consumption.

[0974] 2. Data storage means: The server receives the power usage data sent from the smart plug and stores it in a database (e.g., MySQL, PostgreSQL).

[0975] 3. Data analysis: The server analyzes the collected data to identify energy consumption patterns and wasted standby energy. Data analysis software such as Python or R can be used for data analysis.

[0976] 4. Recommended setting generation method: The server generates on / off settings for energy saving based on the results of data analysis.

[0977] 5. Communication method: The server notifies the user's smartphone or tablet of recommended settings and current energy usage status via an external API such as the LINE API.

[0978] 6. Control: The user's smartphone or tablet controls the smart plug to turn on and off based on the recommended settings received.

[0979] 7. Notification means: The state controlled by the control means is reported to the user via the LINE API.

[0980] Specific examples

[0981] Example 1: Proposal for reducing standby energy consumption at night

[0982] 1. The server analyzes energy consumption data collected overnight and identifies appliances (e.g., televisions) that consume high standby energy.

[0983] 2. Based on the analysis results, the server generates a recommendation to "turn off the TV at night to reduce standby energy consumption."

[0984] 3. Recommended settings will be sent to the user's smartphone via the LINE API.

[0985] 4. Once the user accepts the recommended settings, their smartphone will send an off command to the smart plug.

[0986] 5. The user will be notified via LINE that the TV has been turned off.

[0987] Example prompts to input to the generative AI model

[0988] "Please explain how the smart plug AI system will recommend settings to reduce expensive electricity bills and how it will analyze specific energy consumption data. Please also provide details on how the system will notify users of the recommended settings and the control process that will be implemented after the notification is approved."

[0989] In this way, the present invention realizes efficient management of energy consumption, contributes to reducing household electricity bills, and provides a comfortable living environment.

[0990] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0991] Step 1: User authentication

[0992] The server receives the ID and password entered by the user in the app. For example, let's say the user enters "user123" and "password456".

[0993] Input: User ID and password

[0994] The server checks the received authentication information against the database, specifically to see if the user ID and password match.

[0995] Data processing: User ID and password verification

[0996] Output: Authentication result (success or failure)

[0997] The server returns a success response to the user if authentication is successful, or an error message if authentication is unsuccessful.

[0998] Step 2: Collecting electricity usage data

[0999] The smart plug periodically measures the power consumption of connected appliances (e.g., TV, air conditioner). For example, the TV's power consumption is measured as 150W and the air conditioner's power consumption is measured as 500W.

[1000] Input: Power consumption data for home appliances

[1001] The smart plug sends the measurement results to a server.

[1002] Data processing: Collecting and transmitting power consumption data

[1003] Output: Power consumption data sent to the server

[1004] Step 3: Save your energy usage data

[1005] The server stores the power usage data received from the smart plug in a database. For example, data such as "TV: 150W, Air Conditioner: 500W" is stored for the timestamp "2023-10-01 18:00:00."

[1006] Input: Power consumption data from smart plugs

[1007] Data processing: Saving to database

[1008] Output: Power consumption data stored in a database

[1009] Step 4: Data analysis

[1010] The server periodically analyzes the power usage data stored in the database, for example, identifying high standby power consumption at night based on data from the past week.

[1011] Input: Power usage data stored in the database

[1012] Data processing: Analysis of energy consumption patterns

[1013] Output: Standby energy identification results

[1014] Step 5: Generate recommendations

[1015] Based on the analysis results, the server generates recommended settings to reduce unnecessary energy consumption, such as "turn off the TV between 11:00 PM and 6:00 AM."

[1016] Input: Results of data analysis

[1017] Data Processing: Generating Recommendations

[1018] Output: Recommended settings

[1019] Step 6: Notification of recommended settings

[1020] The server then uses the LINE API to notify the user of the recommended settings on their smartphone, for example, sending a message such as "We recommend turning off the TV at 11:00 PM to reduce standby energy consumption at night."

[1021] Input: Generated recommended settings

[1022] Data processing: Notification content generation

[1023] Output: Notification via LINE API

[1024] Step 7: User Authorization

[1025] The user checks the LINE notification and either approves or rejects the recommended settings. For example, if the user selects "Approve," the approval information is sent to the server.

[1026] Input: LINE notification content

[1027] Data Processing: Accept or Reject

[1028] Output: Approval result

[1029] Step 8: Control your smart plug

[1030] The server, with the user's approval, sends a control command to the smart plug, for example, to turn off the TV at 11:00 PM.

[1031] Input: User approval result

[1032] Data processing: Generation and transmission of control commands

[1033] Output: Control command to the smart plug

[1034] Step 9: Notification of control results

[1035] The server receives the results of the control command from the smart plug and notifies the user via the LINE API. For example, it sends a notification to the user's smartphone saying, "The TV has been successfully turned off."

[1036] Input: Execution result from smart plug

[1037] Data processing: Notification content generation

[1038] Output: Notification via LINE API

[1039] (Application example 1)

[1040] 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."

[1041] There is a lack of means to optimize and efficiently manage power consumption in autonomous vehicles. There is also a need for a system that can quickly and accurately recommend appropriate power usage to drivers and manage it appropriately.

[1042] 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.

[1043] In this invention, the server includes a power metering means connected to each power consumption device, a data storage means for periodically receiving power consumption data from the power metering means and storing the data, a data analysis means for analyzing the power consumption data stored in the data storage means and generating recommended settings for power reduction, a notification means for notifying a user terminal of the recommended settings, a control means for controlling the power supply of each power consumption device based on an instruction from the user terminal, a notification means for notifying a user of a state controlled by the control means, a means for collecting and analyzing power consumption data of each power device in an autonomously driving vehicle, a means for generating recommended settings for optimizing power consumption of the vehicle based on the collected data, a means for notifying an infotainment system of the vehicle of the recommended settings, a means for controlling each power consumption device based on an instruction from the infotainment system, and a means for obtaining approval from the driver to control the device, thereby enabling optimization and efficient management of power consumption in an autonomously driving vehicle.

[1044] A "power measurement means" is a means that is connected to a power-using device and that periodically measures the power consumption of that device.

[1045] The "data storage means" is a means for storing the power usage data received from the power measurement means.

[1046] The "data analysis means" is a means for analyzing the power usage data stored in the data storage means and generating recommended settings for reducing power consumption.

[1047] The "notification means" is a means for notifying the generated recommended settings to the user terminal.

[1048] The "control means" is a means for controlling the power supply of each power consumption device based on instructions from a user terminal.

[1049] An "autonomous vehicle" is a vehicle that can drive autonomously without the need for human operation.

[1050] "Power device" refers to any device in a vehicle that consumes power.

[1051] An "infotainment system" is a system that provides information and entertainment functions within a vehicle.

[1052] The "recommended setting generating means" is a means for generating recommended settings for optimizing power usage based on collected data.

[1053] The "driver approval means" is a means for obtaining approval from the driver for the recommended settings for controlling the power devices.

[1054] This invention is a system for optimizing and efficiently managing power consumption in an autonomous vehicle. This system is composed of a power measurement means, a data storage means, a data analysis means, a notification means, and a control means. The system also works in conjunction with the vehicle's infotainment system to notify the driver of recommended settings for optimized power consumption and automatically control the power supply of devices as needed.

[1055] Hardware and software used

[1056] In-vehicle sensors: Attached to each power device and used to measure power consumption.

[1057] Infotainment system: Used to notify and control the driver.

[1058] Communication module: Handles data communication between the vehicle and the cloud server.

[1059] Cloud data servers (Amazon Web Services, Google Cloud, etc.) analyze data and generate recommended configurations.

[1060] LINE API: Used to send notifications to drivers.

[1061] Program processing overview

[1062] In this system, first, the power measurement means periodically measures the power consumption of each power device and collects data. The data is transmitted to a cloud data server via a communication module and stored in a data storage means. Next, the data analysis means analyzes the data and generates recommended settings to optimize the vehicle's power consumption.

[1063] The generated recommended settings are notified to the driver via notification means. Notification methods include a message notification using the LINE API or a notification on the infotainment system screen. The driver can choose to accept or reject the recommendation, and if accepted, the control means will carry out the appropriate control for each power device. The control status of the power devices is also fed back to the driver via the notification means.

[1064] Specific examples

[1065] Power management during long-distance driving

[1066] System operation flow

[1067] 1. Periodically collect power consumption data from the vehicle's air conditioning and audio systems.

[1068] 2. The collected data is sent to a cloud server in real time and stored in a data storage means.

[1069] 3. The data analysis means analyzes the data and generates recommended settings (e.g., reducing the volume of the audio system, adjusting the air conditioning temperature) to achieve efficient power management during long-distance driving.

[1070] 4. The recommended settings will be notified to the driver via the LINE API or the infotainment system screen.

[1071] 5. If the driver approves the recommended settings, the control means sends control commands to the relevant devices to optimize power usage.

[1072] Prompt Sentence Examples

[1073] "For the next section of the journey, would you like your air conditioning system to lower the temperature by 2 degrees to reduce power consumption? (Yes / No)"

[1074] "Optimizing the volume of your audio system can reduce power consumption. Apply settings? (Yes / No)"

[1075] In this way, the present invention allows for efficient management of power consumption within an autonomous vehicle, optimizing overall power usage and improving operational efficiency.

[1076] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1077] Step 1:

[1078] The power measurement means periodically measures the power consumption of each power device (for example, an air conditioning system or an audio system) and collects the data. This process calculates the power using voltage and current information obtained from the attached sensors and records this as time-series data. The input is voltage and current data, and the output is the power consumption data of each device.

[1079] Step 2:

[1080] The data storage means periodically receives collected power consumption data and transmits it to the cloud server, which stores the received data in a database. The input is the power consumption data from the smart plugs and sensors, and the output is the power consumption records stored in the cloud database.

[1081] Step 3:

[1082] The data analysis means analyzes the power consumption data stored in the database. This includes statistical processing to determine hourly consumption patterns and detect anomalies. Specifically, it uses data mining techniques to identify areas of unnecessary power consumption. The input is the stored power consumption data, and the output is power consumption patterns and recommended optimization settings.

[1083] Step 4:

[1084] The recommended settings generation means generates recommended settings to optimize power consumption based on the analysis results. For example, a setting such as "lower the air conditioning temperature by 2 degrees to reduce power consumption during long-distance driving" is generated. The input is the data analysis results, and the output is the specific recommended settings.

[1085] Step 5:

[1086] The notification means notifies the driver of the generated recommended settings via the LINE API or the infotainment system. The notification content includes an overview of the recommended settings and a message requesting approval. The input is the recommended settings, and the output is a notification to the driver. Specific actions include sending a prompt message via LINE.

[1087] Step 6:

[1088] The user receives a notification and can approve or reject the recommended settings. This approval operation is performed on the infotainment system screen or via LINE message. The input is the notification message, and the output is the response of approval or rejection.

[1089] Step 7:

[1090] The control means controls each power device based on the approved recommended settings, for example, lowering the temperature of the air conditioner or adjusting the volume of the audio system. The input is approval from the user, and the output is a control command to the device.

[1091] Step 8:

[1092] The result of the control performed by the control means is again notified to the driver via the notification means. This notification includes feedback on whether the setting change was successful. The input is the control result, and the output is the feedback notification to the driver.

[1093] This allows power consumption within autonomous vehicles to be optimized and efficiently managed.

[1094] 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.

[1095] This invention combines a smart plug AI system connected to power-using devices in each home with an emotion engine that recognizes the user's emotions, aiming to reduce expensive electricity bills and realize a comfortable lifestyle. This system effectively manages energy consumption and automatically controls on and off, thereby reducing standby power consumption. The emotion engine also recognizes the user's emotional state and provides optimal notifications and control.

[1096] Background and Overview

[1097] Increasing household energy consumption not only puts a strain on household finances but also impacts the environment. To address this issue, the smart plug AI system monitors and manages energy usage via an app on the user's smartphone or tablet, enabling optimal energy consumption. Furthermore, a newly integrated emotion engine recognizes the user's emotional state in real time and provides appropriate notifications accordingly.

[1098] System Configuration

[1099] Power measurement means

[1100] A smart plug is connected to each power-using device and periodically measures its power consumption.

[1101] Data Storage Means

[1102] The server receives the power usage data sent by the smart plug and stores it in a database.

[1103] Data Analysis Methods

[1104] The server analyzes the collected data to identify power consumption patterns and wasted standby power.

[1105] Recommendation Generation

[1106] Based on the results of the data analysis, the server generates recommended settings for reducing power consumption, such as turning off the TV at night.

[1107] Notification means

[1108] The server notifies the user's device of recommended settings and current power usage status via the LINE API.

[1109] Control means

[1110] The user terminal controls the on / off of the smart plug based on the received recommended settings.

[1111] Emotion Engine

[1112] The emotion engine uses sensors such as the camera and microphone installed on the user's smartphone to recognize the user's emotional state (e.g., joy, anger, sadness, surprise, etc.) in real time.

[1113] Program processing overview

[1114] User Authentication

[1115] The server verifies the authentication information entered by the user in the app. When the user enters their ID and password, the information is sent to the server and checked against the database. If the correct information is provided, the user is allowed to access the system.

[1116] Collecting and storing electricity usage data

[1117] The smart plug periodically collects power consumption data from each connected power-using device and sends the data to a server, which stores the data in a database.

[1118] Analyzing data and generating recommendations

[1119] The server periodically analyzes the stored power usage data. Based on the analysis results, it identifies unnecessary standby power consumption and then generates recommendations for reducing it. These recommendations may include scheduling devices to be turned off during certain times of the day or recommending that devices be manually turned off to reduce standby power consumption.

[1120] Emotion Engine Operation

[1121] The emotion engine analyzes the user's emotional state and sends that information to the server. For example, if the user is feeling stressed, the notification message will be adjusted to something more gentle.

[1122] Notification and User Approval

[1123] The generated recommended settings are sent to the user's device via the LINE API. After receiving the notification, the user can choose whether or not to accept the recommended settings. If accepted, a control command is sent to the smart plug.

[1124] Control and Status Notification

[1125] Once the user device approves the recommended settings, the server sends a control command to the smart plug to turn off the power to the target power-using device. The user is again notified of the power-off state via the LINE API.

[1126] Specific examples

[1127] Example 1: Reducing standby power consumption at night and responding to emotional states

[1128] 1. The server analyzes the power consumption data collected overnight and identifies home appliances (e.g., televisions) that consume a lot of standby power.

[1129] 2. Based on the analysis results, the server generates a recommendation to "turn off the TV at night to reduce standby power consumption."

[1130] 3. The emotion engine analyzes the user's emotional state in real time, and if the user is relaxed, for example, the notification content will be changed to a calmer tone.

[1131] 4. Once the user approves the recommended settings notified via the LINE API, the device will send an off command to the smart plug.

[1132] 5. The user will be notified again via LINE notification that the TV has been turned off.

[1133] In this way, the smart plug AI system of the present invention takes into account the user's emotions while efficiently managing and reducing power consumption, contributing to providing a comfortable living environment for users.

[1134] The processing flow will be explained below.

[1135] Step 1:

[1136] The user launches the smartphone app, enters their ID and password on the login screen, and presses the login button.

[1137] Step 2:

[1138] The device sends the user's input information (ID and password) to the server. Specifically, the app calls the server's authentication API and sends the ID and password.

[1139] Step 3:

[1140] The server checks the received ID and password against the user information in the database. The server searches for the user information and, if the data is correct, the authentication is successful.

[1141] Step 4:

[1142] The server returns the authentication result to the terminal. If the authentication is successful, the user proceeds to the next screen, and if the authentication is unsuccessful, an error message is displayed.

[1143] Step 5:

[1144] The smart plug periodically measures the power consumption of the connected power-using device, and the power measurement data is collected at regular intervals.

[1145] Step 6:

[1146] The smart plug sends the measured power consumption data to the server, which uses a specific data transmission protocol.

[1147] Step 7:

[1148] The server stores the received power consumption data in a database, along with a timestamp and device ID.

[1149] Step 8:

[1150] The server analyzes the power consumption data stored in the database. Data analysis algorithms analyze the power consumption patterns of each power-using device and identify wasted standby power.

[1151] Step 9:

[1152] The emotion engine analyzes the user's emotional state. It uses sensors such as the camera and microphone on the user's smartphone to collect emotional data and analyze it in real time.

[1153] Step 10:

[1154] The emotion engine analyzes the emotion data and sends it to the server, providing a basis for tailoring the content of notifications based on the user's emotional state.

[1155] Step 11:

[1156] Based on the analysis, the server generates recommendations for power saving, such as turning off the TV at night.

[1157] Step 12:

[1158] The server notifies the user device of the generated recommended settings, for example, using the LINE API to communicate the recommended settings to the user.

[1159] Step 13:

[1160] The content of notifications is adjusted based on data from the emotion engine. For example, if the user is feeling stressed, the notification content will be changed to a more calming message.

[1161] Step 14:

[1162] The user checks the LINE notification and presses the approve button through the app if they approve the recommended settings. If they reject the settings, they press the reject button.

[1163] Step 15:

[1164] The terminal sends the user's approval or denial to the server, and the server performs the following process depending on the information received:

[1165] Step 16:

[1166] The server sends a control command to the smart plug, for example, "Turn off the TV."

[1167] Step 17:

[1168] The smart plug receives the control command to power off the connected power-using device, and sends a signal back to the server to confirm that the power has been turned off.

[1169] Step 18:

[1170] The server notifies the user device of the control result, and the user is notified via LINE that the power-using device has been turned off.

[1171] Through this series of processes, the smart plug AI system provides an environment where users can easily manage their power usage and efficiently save energy.In addition, the emotion engine provides notifications that take into account the user's emotional state, providing a more personalized experience.

[1172] Example 2

[1173] 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."

[1174] Conventional power management systems have difficulty effectively reducing the standby power consumption of individual power-using devices, resulting in continued wasted power consumption. Furthermore, they lack the ability to respond flexibly to the user's emotional state, limiting the improvement of the user experience.

[1175] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a power measurement means connected to each power consuming device, a data storage means, a data analysis means, a notification means, a control means, a notification means, an emotion engine, and a notification adjustment means. This enables efficient management of power consumption and appropriate notification according to the user's emotional state.

[1176] The "power measurement means" is a device that is connected to each power consuming device and periodically measures the power consumption of that device.

[1177] The "data storage means" is a device or function for storing the power usage data received from the power measurement means.

[1178] The "data analysis means" is a device or function that analyzes the power usage data stored in the data storage means and generates recommended settings for reducing power consumption.

[1179] The "notification means" is a device or function for transmitting recommended settings and power usage information to a user terminal.

[1180] The "control means" is a device or function that controls the power supply of each power consumption device based on instructions from a user terminal.

[1181] An "emotion engine" is a device or function that identifies a user's emotional state in real time and transmits that information to a server.

[1182] The "notification adjustment means" is a device or function that adjusts the notification content based on the emotional state obtained by the emotion engine.

[1183] The "message sending API" is an application programming interface that allows a notification means to send a notification to a user terminal.

[1184] This invention combines a smart plug AI system connected to power-using devices in each home with an emotion engine that recognizes the user's emotions. The goal is to reduce wasteful energy consumption, save on expensive electricity bills, and realize a comfortable lifestyle. This system effectively manages energy consumption and automatically controls on and off, thereby reducing standby power consumption. The emotion engine also recognizes the user's emotional state and provides optimal notifications and control.

[1185] System Configuration

[1186] Power measurement means

[1187] A smart plug connected to each power-using device periodically measures power consumption. For example, a smart plug is connected to each power-using device in a home (refrigerator, TV, air conditioner, etc.).

[1188] Data Storage Means

[1189] The server receives the power usage data sent by the smart plugs and stores it in a database, which includes information such as the power consumption, usage time, and standby power consumption of each device.

[1190] Data Analysis Methods

[1191] The server periodically analyzes the power usage data stored in the database and uses data mining techniques to identify power consumption patterns and generate configuration recommendations to reduce unnecessary standby power consumption.

[1192] Recommendation Generation

[1193] Based on the results of the data analysis, the server generates specific recommendations for power reduction, such as turning off the TV at night or manually turning off unused devices.

[1194] Notification means

[1195] The server notifies the user device of the generated recommended settings and the current power usage status using a message sending API, allowing the user to receive power usage optimization information in real time.

[1196] Control means

[1197] The user device controls the smart plug's on / off state based on the received recommended settings, for example, sending a command to turn off a specific device at night.

[1198] Emotion Engine

[1199] The emotion engine uses sensors such as the camera and microphone on the user's smartphone to recognize the user's emotional state in real time. For example, if the user is feeling stressed, the engine changes the wording of the notification message to something more calming.

[1200] Specific examples

[1201] Example 1: Reducing standby power consumption at night and responding to emotional states

[1202] 1. The server analyzes the power consumption data collected overnight and identifies home appliances (e.g., televisions) that consume a lot of standby power.

[1203] 2. Based on the analysis results, the server generates a recommendation to "turn off the TV at night to reduce standby power consumption."

[1204] 3. The emotion engine analyzes the user's emotional state in real time, and if the user is relaxed, for example, the notification content will be changed to a calmer tone.

[1205] 4. If the user approves the recommended settings, the device sends an off command to the smart plug.

[1206] 5. A notification will again inform the user that the TV has been turned off.

[1207] Examples of prompt statements

[1208] Analyze the power usage of your next device, identify unnecessary standby power consumption, and generate optimal notifications based on the user's emotional state.

[1209] Thus, the system of the present invention has a multi-functional configuration and realizes efficient management and reduction of power consumption while taking into account the emotional state of the user.

[1210] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1211] Step 1:

[1212] (user authentication)

[1213] Specific actions

[1214] Input: The ID and password entered by the user into the app.

[1215] Processing: The server receives the authentication information sent by the user and checks it against the information stored in the database.

[1216] Output: If authentication is successful, an authentication token is issued.

[1217] Operation: If the authentication is successful, the server issues an authentication token to the user and sends it to the user's terminal.

[1218] Step 2:

[1219] (Collection and storage of electricity usage data)

[1220] Specific actions

[1221] Input: Power consumption data that the smart plug periodically obtains from each power-using device.

[1222] Processing: The smart plug collects the data and sends it to the server, which stores it in a database.

[1223] Output: Power usage data stored in a database.

[1224] How it works: The smart plug periodically collects power consumption data from each power-using device and sends it to a server, which stores the data in a database.

[1225] Step 3:

[1226] (Data analysis and generation of recommendations)

[1227] Specific actions

[1228] Input: Power usage data stored in a database.

[1229] Processing: The server uses data mining techniques to analyze power usage patterns, identify unnecessary standby power consumption, and generate power reduction recommendations.

[1230] Output: The generated recommendations.

[1231] How it works: The server analyzes power usage data stored in a database to identify unnecessary standby power consumption, then generates specific recommendations for reducing power consumption.

[1232] Step 4:

[1233] (Emotion engine in action)

[1234] Specific actions

[1235] Input: Emotion data obtained from the user's smartphone (via camera and microphone).

[1236] Processing: The emotion engine analyzes the user's emotional state in real time and sends the information to the server.

[1237] Output: Data about emotional state.

[1238] How it works: The emotion engine collects emotion data from the user's smartphone, analyzes it in real time, and sends the results to the server.

[1239] Step 5:

[1240] (Notification and User Approval)

[1241] Specific actions

[1242] Input: Generated recommendation settings, user emotional state data.

[1243] Processing: The server sends the recommended settings to the user as a notification. The notification content is adjusted based on the emotion data. The user receives the notification and can choose whether to accept the recommended settings.

[1244] Output: User approval or disapproval.

[1245] How it works: The server uses the LINE API or similar to send a notification to the user based on the generated recommended settings and emotion data. The user receives the notification and can choose whether to accept or reject it. If they accept, the information is sent to the server.

[1246] Step 6:

[1247] (control and status notification)

[1248] Specific actions

[1249] Input: Control commands based on user authorization.

[1250] Processing: The server receives the authorization information and sends a control command to the smart plug, which turns off the power of the target device.

[1251] Output: Device powered off state.

[1252] Operation: With the user's approval, the server sends a control command to the smart plug. The smart plug turns off the power to the target power-using device based on the command. It notifies the user again via the LINE API that the device is powered off.

[1253] (Application example 2)

[1254] 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."

[1255] While conventional home energy management systems have focused on reducing and efficiently managing energy consumption, they were unable to provide personalized notifications or suggestions that took into account the user's emotional state. Furthermore, there was a need for a system that could provide a more comfortable and efficient living environment by combining the control of energy-using devices with the user's purchasing experience.

[1256] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes power measurement means connected to each power consumption device, data storage means for periodically receiving power consumption data from the power measurement means and storing the data, data analysis means for analyzing the power consumption data stored in the data storage means and generating recommended settings for power reduction, notification means for notifying a user terminal of the recommended settings, control means for controlling the power supply of each power consumption device based on instructions from the user terminal, notification means for notifying the user of the state controlled by the control means, an emotion engine for analyzing the user's emotions and making optimal product suggestions and notifications based on the analysis results, and recommended setting adjustment means for adjusting the content of the recommended settings based on information from the emotion engine. This makes it possible to efficiently manage power consumption while also providing personalized suggestions and notifications based on the user's emotions.

[1257] The "power measurement means" is a device that is connected to each power consumption device and periodically measures power consumption data.

[1258] The "data storage means" is a device or system that stores the power usage data received from the power measurement means.

[1259] The "data analysis means" is a device or system that analyzes the power usage data stored in the data storage means and generates recommended settings for reducing power consumption.

[1260] The "notification means" is a device or system that notifies the user terminal of recommended settings, power usage status, and the like.

[1261] The "control means" is a device or system that controls the power supply of each power consumption device based on instructions from a user terminal.

[1262] An "emotion engine" is a system or algorithm that analyzes users' emotions and makes optimal product suggestions and notifications based on the analysis results.

[1263] The "recommended settings adjustment means" is a device or system that adjusts the content of recommended settings based on information from the emotion engine.

[1264] This invention combines a smart plug AI system connected to power-using devices in each home with an emotion engine that recognizes the user's emotions. The goal is to reduce expensive electricity bills and realize a comfortable lifestyle. This system effectively manages energy consumption and automatically controls on / off, thereby reducing standby power consumption. The emotion engine also recognizes the user's emotional state and provides optimal notifications and product suggestions accordingly.

[1265] System Configuration

[1266] Power measurement means

[1267] A smart plug is connected to each power-using device and periodically measures its power consumption, sending the measured data to a server.

[1268] Data Storage Means

[1269] The server receives the power usage data sent by the smart plug and stores it in a database for later analysis.

[1270] Data Analysis Methods

[1271] The server analyzes the collected data to identify power consumption patterns and wasted standby power, and generates recommendations for reducing power consumption.

[1272] Notification means

[1273] The server notifies the user device of recommended settings and current power usage status via a common message sending API such as the LINE API.

[1274] Control means

[1275] The user terminal controls the smart plug to turn on and off based on the received recommended settings, and the change in power supply status is reported to the user again via the notification means.

[1276] Emotion Engine

[1277] The emotion engine uses sensors such as the camera and microphone installed on the user's smartphone to recognize the user's emotional state (e.g., joy, anger, sadness, surprise, etc.) in real time. The recognized emotions are sent to the server.

[1278] Recommended settings adjustments

[1279] Based on the user's emotional state provided by the emotion engine, the server adjusts the recommended settings, for example, changing the notification wording to something more gentle if the user is feeling stressed.

[1280] Data processing and calculation

[1281] The program is primarily implemented using Python.

[1282] Facial Recognition and Emotion Analysis: Capture the user's face and analyze their emotions using OpenCV and emotion recognition models (Keras and TensorFlow).

[1283] Data analysis: Use Pandas and NumPy to analyze the electricity usage data stored in the database.

[1284] Notification system: Notify users using LINE API or other common messaging APIs.

[1285] Specific examples

[1286] Example 1: Reducing standby power consumption at night and responding to emotional states

[1287] 1. The server analyzes the power consumption data collected overnight and identifies home appliances (e.g., televisions) that consume a lot of standby power.

[1288] 2. Based on the analysis results, the server generates a recommendation to "turn off the TV at night to reduce standby power consumption."

[1289] 3. The emotion engine analyzes the user's emotional state in real time, and if the user is relaxed, for example, the notification content will be changed to a calmer tone.

[1290] 4. Once the user approves the recommended settings notified via the LINE API, the device will send an off command to the smart plug.

[1291] 5. The user will be notified again via LINE notification that the TV has been turned off.

[1292] Example prompts to input to the generative AI model

[1293] Generate appropriate product suggestions based on user emotions, for example, suggest popular products when the user is happy, or relaxation products when the user is stressed.

[1294] In this way, the smart plug AI system of the present invention takes into account the user's emotions while efficiently managing and reducing power consumption, contributing to providing a comfortable living environment for users.

[1295] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1296] Step 1:

[1297] The server receives periodic power usage data from the smart plug and stores the data in a database. The smart plug is connected to each power-using device and measures power consumption. The measured power usage data is sent to the server and stored in the database for later analysis. The input is the power usage data from the smart plug, and the output is the data stored in the database.

[1298] Step 2:

[1299] The server analyzes the power usage data stored in the database. Specifically, it uses Python libraries such as Pandas and NumPy to identify power consumption patterns and wasteful standby power. The input is the power usage data stored in the database, and the output is recommended settings for power reduction.

[1300] Step 3:

[1301] The server uses a general messaging API such as the LINE API to notify the user device of the generated recommended settings. The input is the recommended settings generated in step 2, and the output is the notification sent to the user device.

[1302] Step 4:

[1303] The emotion engine uses sensors such as the camera and microphone on the user's smartphone to recognize the user's emotional state in real time. For example, it uses OpenCV and an emotion recognition model to analyze emotions from the user's face. The input is sensor data from the smartphone's camera and microphone, and the output is the emotion analysis result.

[1304] Step 5:

[1305] The server adjusts the recommended settings based on the emotional state provided by the emotion engine. For example, if the user is feeling stressed, the notification wording is changed to a more gentle one. The input is the emotion analysis result from the emotion engine, and the output is the adjusted recommended settings.

[1306] Step 6:

[1307] The user terminal controls the on / off of the smart plug based on the received recommended settings after adjustment. The input is the recommended settings after adjustment sent from the server, and the output is the control command for the smart plug.

[1308] Step 7:

[1309] The server then reports the smart plug's control results to the user again using a notification method. For example, it may notify the user via the LINE API that the smart plug has turned off the power-using device. The input is the smart plug's control result, and the output is a notification sent to the user's device.

[1310] 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.

[1311] 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.

[1312] 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.

[1313] [Fourth embodiment]

[1314] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1315] 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.

[1316] 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).

[1317] 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.

[1318] 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.

[1319] 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).

[1320] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1321] 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.

[1322] 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.

[1323] 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.

[1324] 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.

[1325] 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.

[1326] 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."

[1327] This invention is a smart plug AI system that connects to power-using devices in each home to reduce expensive electricity bills and realize a comfortable life. This system effectively manages energy consumption and automatically controls on / off, reducing standby power consumption.

[1328] Background and Overview

[1329] As part of home automation, the smart plug AI system is designed to allow users to easily monitor and control power usage through a smartphone or tablet app. The three parties involved - the server, the device, and the user - work together to achieve efficient power management.

[1330] System Configuration

[1331] 1. Power measurement means: A smart plug is connected to each power-using device and periodically measures its power consumption.

[1332] 2. Data storage means: The server receives the power usage data sent from the smart plug and stores it in a database.

[1333] 3. Data analysis means: The server analyzes the collected data and identifies power consumption patterns and wasted standby power.

[1334] 4. Recommended settings generation: Based on the results of the data analysis, the server generates on / off settings to reduce power consumption.

[1335] 5. Notification method: The server notifies the user device of recommended settings and current power usage status via the LINE API.

[1336] 6. Control means: The user terminal controls the on / off of the smart plug based on the received recommended settings.

[1337] Program processing overview

[1338] User Authentication

[1339] The server verifies the authentication information entered by the user in the app. When the user enters their ID and password, the information is sent to the server and checked against the database. If the correct information is provided, the user is allowed to access the system.

[1340] Collecting and storing electricity usage data

[1341] The smart plug periodically collects power consumption data from each connected power-using device and sends the data to a server, which stores the data in a database.

[1342] Analyzing data and generating recommendations

[1343] The server periodically analyzes the stored power usage data. Based on the analysis results, it identifies unnecessary standby power consumption and then generates recommendations for reducing it. These recommendations may include scheduling devices to be turned off during certain times of the day or recommending that devices be manually turned off to reduce standby power consumption.

[1344] Notification and User Approval

[1345] The generated recommended settings are sent to the user's device via the LINE API. After receiving the notification, the user can choose whether or not to accept the recommended settings. If accepted, a control command is sent to the smart plug.

[1346] Control and Status Notification

[1347] If the user device approves the recommended settings, the server sends a control command to the smart plug to turn off the power to the target power-using device. The user is again notified of the power-off status via the LINE API.

[1348] Specific examples

[1349] Example 1: Proposal for reducing standby power consumption at night

[1350] 1. The server analyzes power consumption data collected overnight and identifies home appliances (e.g., televisions) that consume a lot of standby power.

[1351] 2. Based on the analysis results, the server generates a recommendation to "turn off the TV at night to reduce standby power consumption."

[1352] 3. The settings will be notified to the user via the LINE API.

[1353] 4. If the user approves the recommended settings, the device sends an off command to the smart plug.

[1354] 5. The user will be notified via LINE that the TV has been turned off.

[1355] In this way, the smart plug AI system enables efficient management of power consumption, contributing to reducing household electricity bills and providing a comfortable living environment.

[1356] The processing flow will be explained below.

[1357] Step 1:

[1358] The user launches the smartphone app, enters their ID and password on the login screen, and presses the login button.

[1359] Step 2:

[1360] The device sends the user's input information (ID and password) to the server. Specifically, the app calls the server's authentication API and sends the ID and password.

[1361] Step 3:

[1362] The server checks the received ID and password against the user information in the database. The server searches for the user information and, if the data is correct, the authentication is successful.

[1363] Step 4:

[1364] The server returns the authentication result to the terminal. If the authentication is successful, the user proceeds to the next screen, and if the authentication is unsuccessful, an error message is displayed.

[1365] Step 5:

[1366] The smart plug periodically measures the power consumption of the connected power-using device, and the power measurement data is collected at regular intervals.

[1367] Step 6:

[1368] The smart plug sends the measured power consumption data to the server, which uses a specific data transmission protocol.

[1369] Step 7:

[1370] The server stores the received power consumption data in a database, along with a timestamp and device ID.

[1371] Step 8:

[1372] The server analyzes the power consumption data stored in the database. Data analysis algorithms analyze the power consumption patterns of each power-using device and identify wasted standby power.

[1373] Step 9:

[1374] Based on the analysis, the server generates recommendations for power saving, such as turning off the TV at night.

[1375] Step 10:

[1376] The server notifies the user device of the generated recommended settings using the LINE API, and the user receives a notification of the recommended settings on their smartphone.

[1377] Step 11:

[1378] The user checks the LINE notification and either approves or rejects the recommended settings. If they approve, the user presses the approve button through the app.

[1379] Step 12:

[1380] The device sends the user's approval to the server, which then controls the smart plug based on the approved recommended settings.

[1381] Step 13:

[1382] The server sends a control command to the smart plug, for example, "Turn off the TV."

[1383] Step 14:

[1384] The smart plug receives the control command to power off the connected power-using device, and sends a signal back to the server to confirm that the power has been turned off.

[1385] Step 15:

[1386] The server notifies the user device of the control result, and the user is notified via LINE that the power-using device has been turned off.

[1387] Through this series of processes, the smart plug AI system provides an environment where users can easily manage their power usage and save energy efficiently.

[1388] Example 1

[1389] 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."

[1390] The present invention relates to a technology for effectively managing energy consumption in the home and reducing unnecessary standby energy consumption, thereby saving on expensive electricity bills and realizing a comfortable living environment. However, conventional technologies have the problem of cumbersome management, since users must manually monitor and control each energy-using device. Furthermore, there is an insufficient mechanism for effectively analyzing energy consumption data and generating appropriate recommended settings, which limits the effectiveness of reducing standby energy consumption.

[1391] 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.

[1392] In this invention, the server includes energy measurement means connected to each energy usage device, data storage means for periodically receiving energy usage data from the energy measurement means and storing the data, data analysis means for analyzing the energy usage data stored in the data storage means and generating recommended settings for energy reduction, communication means for notifying a user terminal of the recommended settings, control means for controlling the power supply of each energy usage device based on instructions from the user terminal, and notification means for reporting the status of control by the control means to the user. This makes it possible to automatically and effectively manage energy consumption in the home, thereby reducing the user's effort and saving on expensive electricity bills.

[1393] An "energy measuring means" is a device that is connected to each energy-using device and that periodically measures energy consumption.

[1394] "Data storage means" means a device or system for storing energy usage data received from energy metering means.

[1395] The "data analysis means" is a device or system for analyzing the energy usage data stored in the data storage means and identifying energy consumption patterns and wasted standby energy.

[1396] The "recommended setting generating means" is a device or system for generating recommended settings for energy reduction based on the results of the data analyzing means.

[1397] "Communication means" refers to a device or system for notifying a user terminal of recommended settings and energy usage status.

[1398] The "control means" is a device or system for controlling the power supply of each energy usage device based on instructions from a user terminal.

[1399] The "notification means" is a device or system for reporting the state controlled by the control means to the user.

[1400] "User Device" means a device that allows a User to monitor energy usage and review, approve, or reject recommended settings.

[1401] This invention is a smart plug AI system that connects to energy-using devices in each home to reduce expensive electricity bills and realize a comfortable life. This system effectively manages energy consumption and automatically controls on / off, enabling standby energy reduction.

[1402] System Configuration

[1403] To implement this invention, the following components are required:

[1404] 1. Energy measurement method: Using smart plugs that are connected to each energy-using device and periodically measure power consumption.

[1405] 2. Data storage means: The server receives the power usage data sent from the smart plug and stores it in a database (e.g., MySQL, PostgreSQL).

[1406] 3. Data analysis: The server analyzes the collected data to identify energy consumption patterns and wasted standby energy. Data analysis software such as Python or R can be used for data analysis.

[1407] 4. Recommended setting generation method: The server generates on / off settings for energy saving based on the results of data analysis.

[1408] 5. Communication method: The server notifies the user's smartphone or tablet of recommended settings and current energy usage status via an external API such as the LINE API.

[1409] 6. Control: The user's smartphone or tablet controls the smart plug to turn on and off based on the recommended settings received.

[1410] 7. Notification means: The state controlled by the control means is reported to the user via the LINE API.

[1411] Specific examples

[1412] Example 1: Proposal for reducing standby energy consumption at night

[1413] 1. The server analyzes energy consumption data collected overnight and identifies appliances (e.g., televisions) that consume high standby energy.

[1414] 2. Based on the analysis results, the server generates a recommendation to "turn off the TV at night to reduce standby energy consumption."

[1415] 3. Recommended settings will be sent to the user's smartphone via the LINE API.

[1416] 4. Once the user accepts the recommended settings, their smartphone will send an off command to the smart plug.

[1417] 5. The user will be notified via LINE that the TV has been turned off.

[1418] Example prompts to input to the generative AI model

[1419] "Please explain how the smart plug AI system will recommend settings to reduce expensive electricity bills and how it will analyze specific energy consumption data. Please also provide details on how the system will notify users of the recommended settings and the control process that will be implemented after the notification is approved."

[1420] In this way, the present invention realizes efficient management of energy consumption, contributes to reducing household electricity bills, and provides a comfortable living environment.

[1421] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1422] Step 1: User authentication

[1423] The server receives the ID and password entered by the user in the app. For example, let's say the user enters "user123" and "password456".

[1424] Input: User ID and password

[1425] The server checks the received authentication information against the database, specifically to see if the user ID and password match.

[1426] Data processing: User ID and password verification

[1427] Output: Authentication result (success or failure)

[1428] The server returns a success response to the user if authentication is successful, or an error message if authentication is unsuccessful.

[1429] Step 2: Collecting electricity usage data

[1430] The smart plug periodically measures the power consumption of connected appliances (e.g., TV, air conditioner). For example, the TV's power consumption is measured as 150W and the air conditioner's power consumption is measured as 500W.

[1431] Input: Power consumption data for home appliances

[1432] The smart plug sends the measurement results to a server.

[1433] Data processing: Collecting and transmitting power consumption data

[1434] Output: Power consumption data sent to the server

[1435] Step 3: Save your energy usage data

[1436] The server stores the power usage data received from the smart plug in a database. For example, data such as "TV: 150W, Air Conditioner: 500W" is stored for the timestamp "2023-10-01 18:00:00."

[1437] Input: Power consumption data from smart plugs

[1438] Data processing: Saving to database

[1439] Output: Power consumption data stored in a database

[1440] Step 4: Data analysis

[1441] The server periodically analyzes the power usage data stored in the database, for example, identifying high standby power consumption at night based on data from the past week.

[1442] Input: Power usage data stored in the database

[1443] Data processing: Analysis of energy consumption patterns

[1444] Output: Standby energy identification results

[1445] Step 5: Generate recommendations

[1446] Based on the analysis results, the server generates recommended settings to reduce unnecessary energy consumption, such as "turn off the TV between 11:00 PM and 6:00 AM."

[1447] Input: Results of data analysis

[1448] Data Processing: Generating Recommendations

[1449] Output: Recommended settings

[1450] Step 6: Notification of recommended settings

[1451] The server then uses the LINE API to notify the user of the recommended settings on their smartphone, for example, sending a message such as "We recommend turning off the TV at 11:00 PM to reduce standby energy consumption at night."

[1452] Input: Generated recommended settings

[1453] Data processing: Notification content generation

[1454] Output: Notification via LINE API

[1455] Step 7: User Authorization

[1456] The user checks the LINE notification and either approves or rejects the recommended settings. For example, if the user selects "Approve," the approval information is sent to the server.

[1457] Input: LINE notification content

[1458] Data Processing: Accept or Reject

[1459] Output: Approval result

[1460] Step 8: Control your smart plug

[1461] The server, with the user's approval, sends a control command to the smart plug, for example, to turn off the TV at 11:00 PM.

[1462] Input: User approval result

[1463] Data processing: Generation and transmission of control commands

[1464] Output: Control command to the smart plug

[1465] Step 9: Notification of control results

[1466] The server receives the results of the control command from the smart plug and notifies the user via the LINE API. For example, it sends a notification to the user's smartphone saying, "The TV has been successfully turned off."

[1467] Input: Execution result from smart plug

[1468] Data processing: Notification content generation

[1469] Output: Notification via LINE API

[1470] (Application example 1)

[1471] 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."

[1472] There is a lack of means to optimize and efficiently manage power consumption in autonomous vehicles. There is also a need for a system that can quickly and accurately recommend appropriate power usage to drivers and manage it appropriately.

[1473] 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.

[1474] In this invention, the server includes a power metering means connected to each power consumption device, a data storage means for periodically receiving power consumption data from the power metering means and storing the data, a data analysis means for analyzing the power consumption data stored in the data storage means and generating recommended settings for power reduction, a notification means for notifying a user terminal of the recommended settings, a control means for controlling the power supply of each power consumption device based on an instruction from the user terminal, a notification means for notifying a user of a state controlled by the control means, a means for collecting and analyzing power consumption data of each power device in an autonomously driving vehicle, a means for generating recommended settings for optimizing power consumption of the vehicle based on the collected data, a means for notifying an infotainment system of the vehicle of the recommended settings, a means for controlling each power consumption device based on an instruction from the infotainment system, and a means for obtaining approval from the driver to control the device, thereby enabling optimization and efficient management of power consumption in an autonomously driving vehicle.

[1475] A "power measurement means" is a means that is connected to a power-using device and that periodically measures the power consumption of that device.

[1476] The "data storage means" is a means for storing the power usage data received from the power measurement means.

[1477] The "data analysis means" is a means for analyzing the power usage data stored in the data storage means and generating recommended settings for reducing power consumption.

[1478] The "notification means" is a means for notifying the generated recommended settings to the user terminal.

[1479] The "control means" is a means for controlling the power supply of each power consumption device based on instructions from a user terminal.

[1480] An "autonomous vehicle" is a vehicle that can drive autonomously without the need for human operation.

[1481] "Power device" refers to any device in a vehicle that consumes power.

[1482] An "infotainment system" is a system that provides information and entertainment functions within a vehicle.

[1483] The "recommended setting generating means" is a means for generating recommended settings for optimizing power usage based on collected data.

[1484] The "driver approval means" is a means for obtaining approval from the driver for the recommended settings for controlling the power devices.

[1485] This invention is a system for optimizing and efficiently managing power consumption in an autonomous vehicle. This system is composed of a power measurement means, a data storage means, a data analysis means, a notification means, and a control means. The system also works in conjunction with the vehicle's infotainment system to notify the driver of recommended settings for optimized power consumption and automatically control the power supply of devices as needed.

[1486] Hardware and software used

[1487] In-vehicle sensors: Attached to each power device and used to measure power consumption.

[1488] Infotainment system: Used to notify and control the driver.

[1489] Communication module: Handles data communication between the vehicle and the cloud server.

[1490] Cloud data servers (Amazon Web Services, Google Cloud, etc.) analyze data and generate recommended configurations.

[1491] LINE API: Used to send notifications to drivers.

[1492] Program processing overview

[1493] In this system, first, the power measurement means periodically measures the power consumption of each power device and collects data. The data is transmitted to a cloud data server via a communication module and stored in a data storage means. Next, the data analysis means analyzes the data and generates recommended settings to optimize the vehicle's power consumption.

[1494] The generated recommended settings are notified to the driver via notification means. Notification methods include a message notification using the LINE API or a notification on the infotainment system screen. The driver can choose to accept or reject the recommendation, and if accepted, the control means will carry out the appropriate control for each power device. The control status of the power devices is also fed back to the driver via the notification means.

[1495] Specific examples

[1496] Power management during long-distance driving

[1497] System operation flow

[1498] 1. Periodically collect power consumption data from the vehicle's air conditioning and audio systems.

[1499] 2. The collected data is sent to a cloud server in real time and stored in a data storage means.

[1500] 3. The data analysis means analyzes the data and generates recommended settings (e.g., reducing the volume of the audio system, adjusting the air conditioning temperature) to achieve efficient power management during long-distance driving.

[1501] 4. The recommended settings will be notified to the driver via the LINE API or the infotainment system screen.

[1502] 5. If the driver approves the recommended settings, the control means sends control commands to the relevant devices to optimize power usage.

[1503] Prompt Sentence Examples

[1504] "For the next section of the journey, would you like your air conditioning system to lower the temperature by 2 degrees to reduce power consumption? (Yes / No)"

[1505] "Optimizing the volume of your audio system can reduce power consumption. Apply settings? (Yes / No)"

[1506] In this way, the present invention allows for efficient management of power consumption within an autonomous vehicle, optimizing overall power usage and improving operational efficiency.

[1507] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1508] Step 1:

[1509] The power measurement means periodically measures the power consumption of each power device (for example, an air conditioning system or an audio system) and collects the data. This process calculates the power using voltage and current information obtained from the attached sensors and records this as time-series data. The input is voltage and current data, and the output is the power consumption data of each device.

[1510] Step 2:

[1511] The data storage means periodically receives collected power consumption data and transmits it to the cloud server, which stores the received data in a database. The input is the power consumption data from the smart plugs and sensors, and the output is the power consumption records stored in the cloud database.

[1512] Step 3:

[1513] The data analysis means analyzes the power consumption data stored in the database. This includes statistical processing to determine hourly consumption patterns and detect anomalies. Specifically, it uses data mining techniques to identify areas of unnecessary power consumption. The input is the stored power consumption data, and the output is power consumption patterns and recommended optimization settings.

[1514] Step 4:

[1515] The recommended settings generation means generates recommended settings to optimize power consumption based on the analysis results. For example, a setting such as "lower the air conditioning temperature by 2 degrees to reduce power consumption during long-distance driving" is generated. The input is the data analysis results, and the output is the specific recommended settings.

[1516] Step 5:

[1517] The notification means notifies the driver of the generated recommended settings via the LINE API or the infotainment system. The notification content includes an overview of the recommended settings and a message requesting approval. The input is the recommended settings, and the output is a notification to the driver. Specific actions include sending a prompt message via LINE.

[1518] Step 6:

[1519] The user receives a notification and can approve or reject the recommended settings. This approval operation is performed on the infotainment system screen or via LINE message. The input is the notification message, and the output is the response of approval or rejection.

[1520] Step 7:

[1521] The control means controls each power device based on the approved recommended settings, for example, lowering the temperature of the air conditioner or adjusting the volume of the audio system. The input is approval from the user, and the output is a control command to the device.

[1522] Step 8:

[1523] The result of the control performed by the control means is again notified to the driver via the notification means. This notification includes feedback on whether the setting change was successful. The input is the control result, and the output is the feedback notification to the driver.

[1524] This allows power consumption within autonomous vehicles to be optimized and efficiently managed.

[1525] 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.

[1526] This invention combines a smart plug AI system connected to power-using devices in each home with an emotion engine that recognizes the user's emotions, aiming to reduce expensive electricity bills and realize a comfortable lifestyle. This system effectively manages energy consumption and automatically controls on and off, thereby reducing standby power consumption. The emotion engine also recognizes the user's emotional state and provides optimal notifications and control.

[1527] Background and Overview

[1528] Increasing household energy consumption not only puts a strain on household finances but also impacts the environment. To address this issue, the smart plug AI system monitors and manages energy usage via an app on the user's smartphone or tablet, enabling optimal energy consumption. Furthermore, a newly integrated emotion engine recognizes the user's emotional state in real time and provides appropriate notifications accordingly.

[1529] System Configuration

[1530] Power measurement means

[1531] A smart plug is connected to each power-using device and periodically measures its power consumption.

[1532] Data Storage Means

[1533] The server receives the power usage data sent by the smart plug and stores it in a database.

[1534] Data Analysis Methods

[1535] The server analyzes the collected data to identify power consumption patterns and wasted standby power.

[1536] Recommendation Generation

[1537] Based on the results of the data analysis, the server generates recommended settings for reducing power consumption, such as turning off the TV at night.

[1538] Notification means

[1539] The server notifies the user's device of recommended settings and current power usage status via the LINE API.

[1540] Control means

[1541] The user terminal controls the on / off of the smart plug based on the received recommended settings.

[1542] Emotion Engine

[1543] The emotion engine uses sensors such as the camera and microphone installed on the user's smartphone to recognize the user's emotional state (e.g., joy, anger, sadness, surprise, etc.) in real time.

[1544] Program processing overview

[1545] User Authentication

[1546] The server verifies the authentication information entered by the user in the app. When the user enters their ID and password, the information is sent to the server and checked against the database. If the correct information is provided, the user is allowed to access the system.

[1547] Collecting and storing electricity usage data

[1548] The smart plug periodically collects power consumption data from each connected power-using device and sends the data to a server, which stores the data in a database.

[1549] Analyzing data and generating recommendations

[1550] The server periodically analyzes the stored power usage data. Based on the analysis results, it identifies unnecessary standby power consumption and then generates recommendations for reducing it. These recommendations may include scheduling devices to be turned off during certain times of the day or recommending that devices be manually turned off to reduce standby power consumption.

[1551] Emotion Engine Operation

[1552] The emotion engine analyzes the user's emotional state and sends that information to the server. For example, if the user is feeling stressed, the notification message will be adjusted to something more gentle.

[1553] Notification and User Approval

[1554] The generated recommended settings are sent to the user's device via the LINE API. After receiving the notification, the user can choose whether or not to accept the recommended settings. If accepted, a control command is sent to the smart plug.

[1555] Control and Status Notification

[1556] Once the user device approves the recommended settings, the server sends a control command to the smart plug to turn off the power to the target power-using device. The user is again notified of the power-off state via the LINE API.

[1557] Specific examples

[1558] Example 1: Reducing standby power consumption at night and responding to emotional states

[1559] 1. The server analyzes the power consumption data collected overnight and identifies home appliances (e.g., televisions) that consume a lot of standby power.

[1560] 2. Based on the analysis results, the server generates a recommendation to "turn off the TV at night to reduce standby power consumption."

[1561] 3. The emotion engine analyzes the user's emotional state in real time, and if the user is relaxed, for example, the notification content will be changed to a calmer tone.

[1562] 4. Once the user approves the recommended settings notified via the LINE API, the device will send an off command to the smart plug.

[1563] 5. The user will be notified again via LINE notification that the TV has been turned off.

[1564] In this way, the smart plug AI system of the present invention takes into account the user's emotions while efficiently managing and reducing power consumption, contributing to providing a comfortable living environment for users.

[1565] The processing flow will be explained below.

[1566] Step 1:

[1567] The user launches the smartphone app, enters their ID and password on the login screen, and presses the login button.

[1568] Step 2:

[1569] The device sends the user's input information (ID and password) to the server. Specifically, the app calls the server's authentication API and sends the ID and password.

[1570] Step 3:

[1571] The server checks the received ID and password against the user information in the database. The server searches for the user information and, if the data is correct, the authentication is successful.

[1572] Step 4:

[1573] The server returns the authentication result to the terminal. If the authentication is successful, the user proceeds to the next screen, and if the authentication is unsuccessful, an error message is displayed.

[1574] Step 5:

[1575] The smart plug periodically measures the power consumption of the connected power-using device, and the power measurement data is collected at regular intervals.

[1576] Step 6:

[1577] The smart plug sends the measured power consumption data to the server, which uses a specific data transmission protocol.

[1578] Step 7:

[1579] The server stores the received power consumption data in a database, along with a timestamp and device ID.

[1580] Step 8:

[1581] The server analyzes the power consumption data stored in the database. Data analysis algorithms analyze the power consumption patterns of each power-using device and identify wasted standby power.

[1582] Step 9:

[1583] The emotion engine analyzes the user's emotional state. It uses sensors such as the camera and microphone on the user's smartphone to collect emotional data and analyze it in real time.

[1584] Step 10:

[1585] The emotion engine analyzes the emotion data and sends it to the server, providing a basis for tailoring the content of notifications based on the user's emotional state.

[1586] Step 11:

[1587] Based on the analysis, the server generates recommendations for power saving, such as turning off the TV at night.

[1588] Step 12:

[1589] The server notifies the user device of the generated recommended settings, for example, using the LINE API to communicate the recommended settings to the user.

[1590] Step 13:

[1591] The content of notifications is adjusted based on data from the emotion engine. For example, if the user is feeling stressed, the notification content will be changed to a more calming message.

[1592] Step 14:

[1593] The user checks the LINE notification and presses the approve button through the app if they approve the recommended settings. If they reject the settings, they press the reject button.

[1594] Step 15:

[1595] The terminal sends the user's approval or denial to the server, and the server performs the following process depending on the information received:

[1596] Step 16:

[1597] The server sends a control command to the smart plug, for example, "Turn off the TV."

[1598] Step 17:

[1599] The smart plug receives the control command to power off the connected power-using device, and sends a signal back to the server to confirm that the power has been turned off.

[1600] Step 18:

[1601] The server notifies the user device of the control result, and the user is notified via LINE that the power-using device has been turned off.

[1602] Through this series of processes, the smart plug AI system provides an environment where users can easily manage their power usage and efficiently save energy.In addition, the emotion engine provides notifications that take into account the user's emotional state, providing a more personalized experience.

[1603] Example 2

[1604] 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."

[1605] Conventional power management systems have difficulty effectively reducing the standby power consumption of individual power-using devices, resulting in continued wasted power consumption. Furthermore, they lack the ability to respond flexibly to the user's emotional state, limiting the improvement of the user experience.

[1606] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a power measurement means connected to each power consuming device, a data storage means, a data analysis means, a notification means, a control means, a notification means, an emotion engine, and a notification adjustment means. This enables efficient management of power consumption and appropriate notification according to the user's emotional state.

[1607] The "power measurement means" is a device that is connected to each power consuming device and periodically measures the power consumption of that device.

[1608] The "data storage means" is a device or function for storing the power usage data received from the power measurement means.

[1609] The "data analysis means" is a device or function that analyzes the power usage data stored in the data storage means and generates recommended settings for reducing power consumption.

[1610] The "notification means" is a device or function for transmitting recommended settings and power usage information to a user terminal.

[1611] The "control means" is a device or function that controls the power supply of each power consumption device based on instructions from a user terminal.

[1612] An "emotion engine" is a device or function that identifies a user's emotional state in real time and transmits that information to a server.

[1613] The "notification adjustment means" is a device or function that adjusts the notification content based on the emotional state obtained by the emotion engine.

[1614] The "message sending API" is an application programming interface that allows a notification means to send a notification to a user terminal.

[1615] This invention combines a smart plug AI system connected to power-using devices in each home with an emotion engine that recognizes the user's emotions. The goal is to reduce wasteful energy consumption, save on expensive electricity bills, and realize a comfortable lifestyle. This system effectively manages energy consumption and automatically controls on and off, thereby reducing standby power consumption. The emotion engine also recognizes the user's emotional state and provides optimal notifications and control.

[1616] System Configuration

[1617] Power measurement means

[1618] A smart plug connected to each power-using device periodically measures power consumption. For example, a smart plug is connected to each power-using device in a home (refrigerator, TV, air conditioner, etc.).

[1619] Data Storage Means

[1620] The server receives the power usage data sent by the smart plugs and stores it in a database, which includes information such as the power consumption, usage time, and standby power consumption of each device.

[1621] Data Analysis Methods

[1622] The server periodically analyzes the power usage data stored in the database and uses data mining techniques to identify power consumption patterns and generate configuration recommendations to reduce unnecessary standby power consumption.

[1623] Recommendation Generation

[1624] Based on the results of the data analysis, the server generates specific recommendations for power reduction, such as turning off the TV at night or manually turning off unused devices.

[1625] Notification means

[1626] The server notifies the user device of the generated recommended settings and the current power usage status using a message sending API, allowing the user to receive power usage optimization information in real time.

[1627] Control means

[1628] The user device controls the smart plug's on / off state based on the received recommended settings, for example, sending a command to turn off a specific device at night.

[1629] Emotion Engine

[1630] The emotion engine uses sensors such as the camera and microphone on the user's smartphone to recognize the user's emotional state in real time. For example, if the user is feeling stressed, the engine changes the wording of the notification message to something more calming.

[1631] Specific examples

[1632] Example 1: Reducing standby power consumption at night and responding to emotional states

[1633] 1. The server analyzes the power consumption data collected overnight and identifies home appliances (e.g., televisions) that consume a lot of standby power.

[1634] 2. Based on the analysis results, the server generates a recommendation to "turn off the TV at night to reduce standby power consumption."

[1635] 3. The emotion engine analyzes the user's emotional state in real time, and if the user is relaxed, for example, the notification content will be changed to a calmer tone.

[1636] 4. If the user approves the recommended settings, the device sends an off command to the smart plug.

[1637] 5. A notification will again inform the user that the TV has been turned off.

[1638] Examples of prompt statements

[1639] Analyze the power usage of your next device, identify unnecessary standby power consumption, and generate optimal notifications based on the user's emotional state.

[1640] Thus, the system of the present invention has a multi-functional configuration and realizes efficient management and reduction of power consumption while taking into account the emotional state of the user.

[1641] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1642] Step 1:

[1643] (user authentication)

[1644] Specific actions

[1645] Input: The ID and password entered by the user into the app.

[1646] Processing: The server receives the authentication information sent by the user and checks it against the information stored in the database.

[1647] Output: If authentication is successful, an authentication token is issued.

[1648] Operation: If the authentication is successful, the server issues an authentication token to the user and sends it to the user's terminal.

[1649] Step 2:

[1650] (Collection and storage of electricity usage data)

[1651] Specific actions

[1652] Input: Power consumption data that the smart plug periodically obtains from each power-using device.

[1653] Processing: The smart plug collects the data and sends it to the server, which stores it in a database.

[1654] Output: Power usage data stored in a database.

[1655] How it works: The smart plug periodically collects power consumption data from each power-using device and sends it to a server, which stores the data in a database.

[1656] Step 3:

[1657] (Data analysis and generation of recommendations)

[1658] Specific actions

[1659] Input: Power usage data stored in a database.

[1660] Processing: The server uses data mining techniques to analyze power usage patterns, identify unnecessary standby power consumption, and generate power reduction recommendations.

[1661] Output: The generated recommendations.

[1662] How it works: The server analyzes power usage data stored in a database to identify unnecessary standby power consumption, then generates specific recommendations for reducing power consumption.

[1663] Step 4:

[1664] (Emotion engine in action)

[1665] Specific actions

[1666] Input: Emotion data obtained from the user's smartphone (via camera and microphone).

[1667] Processing: The emotion engine analyzes the user's emotional state in real time and sends the information to the server.

[1668] Output: Data about emotional state.

[1669] How it works: The emotion engine collects emotion data from the user's smartphone, analyzes it in real time, and sends the results to the server.

[1670] Step 5:

[1671] (Notification and User Approval)

[1672] Specific actions

[1673] Input: Generated recommendation settings, user emotional state data.

[1674] Processing: The server sends the recommended settings to the user as a notification. The notification content is adjusted based on the emotion data. The user receives the notification and can choose whether to accept the recommended settings.

[1675] Output: User approval or disapproval.

[1676] How it works: The server uses the LINE API or similar to send a notification to the user based on the generated recommended settings and emotion data. The user receives the notification and can choose whether to accept or reject it. If they accept, the information is sent to the server.

[1677] Step 6:

[1678] (control and status notification)

[1679] Specific actions

[1680] Input: Control commands based on user authorization.

[1681] Processing: The server receives the authorization information and sends a control command to the smart plug, which turns off the power of the target device.

[1682] Output: Device powered off state.

[1683] Operation: With the user's approval, the server sends a control command to the smart plug. The smart plug turns off the power to the target power-using device based on the command. It notifies the user again via the LINE API that the device is powered off.

[1684] (Application example 2)

[1685] 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."

[1686] While conventional home energy management systems have focused on reducing and efficiently managing energy consumption, they were unable to provide personalized notifications or suggestions that took into account the user's emotional state. Furthermore, there was a need for a system that could provide a more comfortable and efficient living environment by combining the control of energy-using devices with the user's purchasing experience.

[1687] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes power measurement means connected to each power consumption device, data storage means for periodically receiving power consumption data from the power measurement means and storing the data, data analysis means for analyzing the power consumption data stored in the data storage means and generating recommended settings for power reduction, notification means for notifying a user terminal of the recommended settings, control means for controlling the power supply of each power consumption device based on instructions from the user terminal, notification means for notifying the user of the state controlled by the control means, an emotion engine for analyzing the user's emotions and making optimal product suggestions and notifications based on the analysis results, and recommended setting adjustment means for adjusting the content of the recommended settings based on information from the emotion engine. This makes it possible to efficiently manage power consumption while also providing personalized suggestions and notifications based on the user's emotions.

[1688] The "power measurement means" is a device that is connected to each power consumption device and periodically measures power consumption data.

[1689] The "data storage means" is a device or system that stores the power usage data received from the power measurement means.

[1690] The "data analysis means" is a device or system that analyzes the power usage data stored in the data storage means and generates recommended settings for reducing power consumption.

[1691] The "notification means" is a device or system that notifies the user terminal of recommended settings, power usage status, and the like.

[1692] The "control means" is a device or system that controls the power supply of each power consumption device based on instructions from a user terminal.

[1693] An "emotion engine" is a system or algorithm that analyzes users' emotions and makes optimal product suggestions and notifications based on the analysis results.

[1694] The "recommended settings adjustment means" is a device or system that adjusts the content of recommended settings based on information from the emotion engine.

[1695] This invention combines a smart plug AI system connected to power-using devices in each home with an emotion engine that recognizes the user's emotions. The goal is to reduce expensive electricity bills and realize a comfortable lifestyle. This system effectively manages energy consumption and automatically controls on / off, thereby reducing standby power consumption. The emotion engine also recognizes the user's emotional state and provides optimal notifications and product suggestions accordingly.

[1696] System Configuration

[1697] Power measurement means

[1698] A smart plug is connected to each power-using device and periodically measures its power consumption, sending the measured data to a server.

[1699] Data Storage Means

[1700] The server receives the power usage data sent by the smart plug and stores it in a database for later analysis.

[1701] Data Analysis Methods

[1702] The server analyzes the collected data to identify power consumption patterns and wasted standby power, and generates recommendations for reducing power consumption.

[1703] Notification means

[1704] The server notifies the user device of recommended settings and current power usage status via a common message sending API such as the LINE API.

[1705] Control means

[1706] The user terminal controls the smart plug to turn on and off based on the received recommended settings, and the change in power supply status is reported to the user again via the notification means.

[1707] Emotion Engine

[1708] The emotion engine uses sensors such as the camera and microphone installed on the user's smartphone to recognize the user's emotional state (e.g., joy, anger, sadness, surprise, etc.) in real time. The recognized emotions are sent to the server.

[1709] Recommended settings adjustments

[1710] Based on the user's emotional state provided by the emotion engine, the server adjusts the recommended settings, for example, changing the notification wording to something more gentle if the user is feeling stressed.

[1711] Data processing and calculation

[1712] The program is primarily implemented using Python.

[1713] Facial Recognition and Emotion Analysis: Capture the user's face and analyze their emotions using OpenCV and emotion recognition models (Keras and TensorFlow).

[1714] Data analysis: Use Pandas and NumPy to analyze the electricity usage data stored in the database.

[1715] Notification system: Notify users using LINE API or other common messaging APIs.

[1716] Specific examples

[1717] Example 1: Reducing standby power consumption at night and responding to emotional states

[1718] 1. The server analyzes the power consumption data collected overnight and identifies home appliances (e.g., televisions) that consume a lot of standby power.

[1719] 2. Based on the analysis results, the server generates a recommendation to "turn off the TV at night to reduce standby power consumption."

[1720] 3. The emotion engine analyzes the user's emotional state in real time, and if the user is relaxed, for example, the notification content will be changed to a calmer tone.

[1721] 4. Once the user approves the recommended settings notified via the LINE API, the device will send an off command to the smart plug.

[1722] 5. The user will be notified again via LINE notification that the TV has been turned off.

[1723] Example prompts to input to the generative AI model

[1724] Generate appropriate product suggestions based on user emotions, for example, suggest popular products when the user is happy, or relaxation products when the user is stressed.

[1725] In this way, the smart plug AI system of the present invention takes into account the user's emotions while efficiently managing and reducing power consumption, contributing to providing a comfortable living environment for users.

[1726] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1727] Step 1:

[1728] The server receives periodic power usage data from the smart plug and stores the data in a database. The smart plug is connected to each power-using device and measures power consumption. The measured power usage data is sent to the server and stored in the database for later analysis. The input is the power usage data from the smart plug, and the output is the data stored in the database.

[1729] Step 2:

[1730] The server analyzes the power usage data stored in the database. Specifically, it uses Python libraries such as Pandas and NumPy to identify power consumption patterns and wasteful standby power. The input is the power usage data stored in the database, and the output is recommended settings for power reduction.

[1731] Step 3:

[1732] The server uses a general messaging API such as the LINE API to notify the user device of the generated recommended settings. The input is the recommended settings generated in step 2, and the output is the notification sent to the user device.

[1733] Step 4:

[1734] The emotion engine uses sensors such as the camera and microphone on the user's smartphone to recognize the user's emotional state in real time. For example, it uses OpenCV and an emotion recognition model to analyze emotions from the user's face. The input is sensor data from the smartphone's camera and microphone, and the output is the emotion analysis result.

[1735] Step 5:

[1736] The server adjusts the recommended settings based on the emotional state provided by the emotion engine. For example, if the user is feeling stressed, the notification wording is changed to a more gentle one. The input is the emotion analysis result from the emotion engine, and the output is the adjusted recommended settings.

[1737] Step 6:

[1738] The user terminal controls the on / off of the smart plug based on the received recommended settings after adjustment. The input is the recommended settings after adjustment sent from the server, and the output is the control command for the smart plug.

[1739] Step 7:

[1740] The server then reports the smart plug's control results to the user again using a notification method. For example, it may notify the user via the LINE API that the smart plug has turned off the power-using device. The input is the smart plug's control result, and the output is a notification sent to the user's device.

[1741] 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.

[1742] 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.

[1743] 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.

[1744] 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.

[1745] 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.

[1746] 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.

[1747] 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).

[1748] 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.

[1749] 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."

[1750] 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.

[1751] 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).

[1752] 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.

[1753] 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.

[1754] 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.

[1755] 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.

[1756] 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.

[1757] 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.

[1758] 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.

[1759] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1760] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1761] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1762] The following is further disclosed regarding the above embodiment.

[1763] (Claim 1)

[1764] power measurement means connected to each of the power consumption devices;

[1765] a data storage means for periodically receiving power usage data from the power measurement means and storing the data;

[1766] data analysis means for analyzing the power usage data stored in the data storage means and generating recommended settings for power reduction;

[1767] a notification means for notifying a user terminal of the recommended settings;

[1768] a control means for controlling the power supply of each of the power consumption devices based on an instruction from the user terminal;

[1769] a notification means for notifying a user of a state controlled by the control means;

[1770] A system including:

[1771] (Claim 2)

[1772] The system of claim 1 further comprises a recommended setting generation means for identifying power-consuming devices that consume a lot of standby power at night based on the power usage data stored in the data storage means, and providing recommended settings for powering them off based on the identified power usage data.

[1773] (Claim 3)

[1774] 2. The system according to claim 1, wherein the notification means further comprises means for sending a notification to the user terminal using a LINE API.

[1775] "Example 1"

[1776] (Claim 1)

[1777] an energy measuring means connected to each of the power consuming devices;

[1778] a data storage means for periodically receiving energy usage data from the energy measurement means and storing the data;

[1779] data analysis means for analyzing the energy usage data stored in the data storage means and generating recommended settings for energy reduction;

[1780] a communication means for notifying a user terminal of the recommended settings;

[1781] a control means for controlling a power supply of each of the energy usage devices based on an instruction from the user terminal;

[1782] a notification means for reporting to a user the state controlled by the control means;

[1783] A system including:

[1784] (Claim 2)

[1785] The system of claim 1 further comprises a recommended setting generation means for identifying energy-using devices that have high standby energy at night based on the energy usage data stored in the data storage means, and providing recommended settings for powering them off based on the identified energy-using devices.

[1786] (Claim 3)

[1787] 2. The system according to claim 1, wherein the communication means further comprises means for sending a notification to the user terminal using an external API.

[1788] "Application Example 1"

[1789] (Claim 1)

[1790] power measurement means connected to each of the power consumption devices;

[1791] a data storage means for periodically receiving power usage data from the power measurement means and storing the data;

[1792] data analysis means for analyzing the power usage data stored in the data storage means and generating recommended settings for power reduction;

[1793] a notification means for notifying a user terminal of the recommended settings;

[1794] a control means for controlling the power supply of each of the power consumption devices based on an instruction from the user terminal;

[1795] a notification means for notifying a user of a state controlled by the control means;

[1796] a means for collecting and analyzing power usage data for each power device in the autonomous vehicle;

[1797] means for generating recommended settings for optimizing power usage of the vehicle based on the collected data;

[1798] means for communicating the recommended settings to a vehicle infotainment system;

[1799] means for controlling each power device based on an instruction from an infotainment system;

[1800] means for obtaining approval from a driver to control said device;

[1801] A system including:

[1802] (Claim 2)

[1803] 2. The system according to claim 1, further comprising a recommended setting generating means for suggesting efficient power management during long-distance driving based on the power usage data stored in the data storage means.

[1804] (Claim 3)

[1805] 2. The system of claim 1, wherein the notification means further comprises means for presenting recommended settings for reducing power consumption to the driver through an infotainment system.

[1806] "Example 2: Combining Emotion Engines"

[1807] (Claim 1)

[1808] power measurement means connected to each of the power consumption devices;

[1809] a data storage means for periodically receiving power usage data from the power measurement means and storing the data;

[1810] data analysis means for analyzing the power usage data stored in the data storage means and generating recommended settings for power reduction;

[1811] a notification means for notifying a user terminal of the recommended settings;

[1812] a control means for controlling the power supply of each of the power consumption devices based on an instruction from the user terminal;

[1813] a notification means for notifying a user of a state controlled by the control means;

[1814] an emotion engine that analyzes the user's emotional state;

[1815] a notification adjusting means for adjusting notification content based on the emotional state obtained by the emotion engine;

[1816] A system including:

[1817] (Claim 2)

[1818] The system of claim 1 further comprises a recommended setting generation means for identifying power-consuming devices that consume a lot of standby power at night based on the power usage data stored in the data storage means, and providing recommended settings for powering them off based on the identified power usage data.

[1819] (Claim 3)

[1820] 2. The system according to claim 1, wherein the notification means further comprises means for sending a notification to the user terminal using a message transmission API.

[1821] "Application example 2 when combining emotion engines"

[1822] (Claim 1)

[1823] power measurement means connected to each of the power consumption devices;

[1824] a data storage means for periodically receiving power usage data from the power measurement means and storing the data;

[1825] data analysis means for analyzing the power usage data stored in the data storage means and generating recommended settings for power reduction;

[1826] a notification means for notifying a user terminal of the recommended settings;

[1827] a control means for controlling the power supply of each of the power consumption devices based on an instruction from the user terminal;

[1828] a notification means for notifying a user of a state controlled by the control means;

[1829] An emotion engine that analyzes user emotions and makes optimal product suggestions and notifications based on the analysis results;

[1830] a recommended setting adjustment means for adjusting the content of the recommended setting based on information from the emotion engine;

[1831] A system including:

[1832] (Claim 2)

[1833] The system of claim 1 further comprises a recommended setting generation means for identifying power-consuming devices that consume a lot of standby power at night based on the power usage data stored in the data storage means, and providing recommended settings for powering them off based on the identified power usage data.

[1834] (Claim 3)

[1835] 2. The system according to claim 1, wherein the notification means further comprises means for sending a notification to the user terminal using a general message transmission API. [Explanation of symbols]

[1836] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. power measurement means connected to each of the power consumption devices; a data storage means for periodically receiving power usage data from the power measurement means and storing the data; data analysis means for analyzing the power usage data stored in the data storage means and generating recommended settings for power reduction; a notification means for notifying a user terminal of the recommended settings; a control means for controlling the power supply of each of the power consumption devices based on an instruction from the user terminal; a notification means for notifying a user of a state controlled by the control means; A system including:

2. The system of claim 1 further comprises a recommended setting generation means for identifying power-consuming devices that consume a lot of standby power at night based on the power usage data stored in the data storage means, and providing recommended settings for powering them off based on this.

3. The system according to claim 1 , wherein the notification means further comprises means for sending a notification to the user terminal using a LINE API.

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