Electronic device, and method for providing response of electronic device to user input

Abstract

In an embodiment of the present disclosure, an electronic device may comprise a communication circuit, a memory for storing instructions, and at least one processor. The instructions, when executed by the at least one processor, may cause the electronic device to: acquire a user input for acquiring information; on the basis of user information, determine a level of a response including the information; on the basis of at least a portion of the user information, recognize types of a plurality of pieces of data related to the information; request data corresponding to the recognized type from at least one external electronic device in order to provide a response of the determined level; on the basis of the request, receive at least one piece of first data from the at least one external electronic device; and on the basis of the received at least one piece of first data, provide a response including the information, corresponding to the determined level.

Description

Methods for providing electronic devices and responses to user input from electronic devices

[0001] Embodiments disclosed in this document relate to an electronic device and a method for providing a response to user input of the electronic device.

[0002] An electronic device can receive data related to user input from an external electronic device. The electronic device can then use the data received from the external electronic device to provide a response to the user's input. Furthermore, the electronic device can generate a response to the user's question using the acquired information using a large language model (LLM).

[0003] The above information may be provided as background art to aid in understanding the present disclosure. No claim or determination is made as to whether any of the above is applicable as prior art in connection with the present disclosure.

[0004] In one embodiment of the present disclosure, an electronic device may include a communication circuit, a memory storing instructions, and at least one processor. The instructions, when executed by the at least one processor, may cause the electronic device to obtain a user input for obtaining information, determine a level of a response including the information based on the user information, identify a plurality of types of data related to the information based at least in part on the user information, transmit a request to at least one external electronic device for requesting data corresponding to the identified types to provide a response of the determined level, receive at least one first data from the at least one external electronic device based on the request, and provide a response including the information and corresponding to the determined level based on the received at least one first data. The user information may include at least one of a history of a user input related to the information, a history of a response of the electronic device related to the information, or user feedback regarding a response of the electronic device related to the information.

[0005] A method for providing a response to a user input of an electronic device according to one embodiment disclosed in the present document may include an operation of obtaining a user input for obtaining information, an operation of determining a level of a response including the information based on user information, an operation of identifying a plurality of types of data related to the information based at least in part on the user information, an operation of transmitting a request for requesting data corresponding to the identified types to at least one external electronic device to provide a response of the determined level, an operation of receiving at least one first data from the at least one external electronic device based on the request, and an operation of providing a response including the information and corresponding to the determined level based on the received at least one first data. The user information may include at least one of a history of a user input related to the information, a history of a response of the electronic device related to the information, or a user's feedback on a response of the electronic device related to the information.

[0006] A computer-readable storage medium according to an embodiment disclosed in the present document may store instructions. The instructions, when executed by at least one processor, may cause the at least one processor to obtain a user input for obtaining information, determine a level of a response including the information based on the user information, identify a plurality of types of data related to the information based at least in part on the user information, request data corresponding to the identified types from at least one external electronic device to provide a response of the determined level, receive at least one first data from the at least one external electronic device based on the request, and provide a response including the information and corresponding to the determined level based on the received at least one first data. The user information may include at least one of a history of a user input related to the information, a history of a response of the electronic device related to the information, or user feedback regarding a response of the electronic device related to the information.

[0007] FIG. 1 is a system diagram for an electronic device to provide a response to a user input to a user, according to one embodiment of the present disclosure.

[0008] FIG. 2 is a block diagram of a configuration of an electronic device according to one embodiment of the present disclosure.

[0009] FIG. 3 is a block diagram of the configuration of an AI model according to one embodiment of the present disclosure.

[0010] FIG. 4 is a flowchart of a method for an electronic device to provide a response corresponding to a user input, according to one embodiment of the present disclosure.

[0011] FIGS. 5A and 5B are diagrams related to an electronic device providing a response based on user information, according to one embodiment of the present disclosure.

[0012] FIGS. 6A and 6B are diagrams showing data measured by an external electronic device in the form of graphs according to one embodiment of the present disclosure.

[0013] FIG. 7 is a flowchart for an electronic device to provide a response to a user input according to one embodiment of the present disclosure.

[0014] FIG. 8 is a signal flow diagram between an electronic device and at least one external electronic device for providing a response to a user input, according to one embodiment of the present disclosure.

[0015] FIG. 9 is a signal flow diagram between an electronic device and a plurality of external electronic devices for providing a response to a user input according to one embodiment of the present disclosure.

[0016] FIG. 10 is a diagram illustrating a method for an electronic device to change a data measurement setting value of an external electronic device according to one embodiment of the present disclosure.

[0017] FIG. 11 is a diagram illustrating an electronic device determining a weight of data based on a user's usage pattern for multiple external electronic devices, according to one embodiment of the present disclosure.

[0018] FIG. 12 is a block diagram of an electronic device within a network environment according to various embodiments.

[0019] In connection with the description of the drawings, the same or similar reference numerals may be used for identical or similar components.

[0020] Hereinafter, various embodiments of the present invention will be described with reference to the accompanying drawings. However, this is not intended to limit the present invention to specific embodiments, and it should be understood that various modifications, equivalents, and / or alternatives of the embodiments of the present invention are included.

[0021] FIG. 1 is a system diagram for an electronic device to provide a response to a user input to a user, according to one embodiment of the present disclosure.

[0022] In one embodiment of the present disclosure, the electronic device (10) can communicate with at least one external electronic device (e.g., a first external electronic device (20a), a second external electronic device (20b)). In one example, the electronic device (10) can communicate with the at least one external electronic device via a network (not shown). In one example, the electronic device (10) can communicate with the at least one external electronic device via a direct connection (e.g., a wired connection and / or an end-to-end wireless connection). For example, the electronic device (10) and / or the at least one external electronic device can include any electronic device such as a smartphone, a laptop, a desktop, a TV, a smart pad, a tablet PC, a connected car, home appliances, various IoT (Internet of Things) devices based on the Internet of Things (e.g., a home IoT device), and / or a portable terminal. For example, the electronic device (10) and / or at least one external electronic device may include any form of wearable device that can be worn by a user, such as a smart watch, a smart band, smart glasses, smart earphones, a smart ring, a smart patch, and / or a smart necklace.

[0023] Hereinafter, a person skilled in the art will understand that the description related to the first external electronic device (20a) can be similarly applied to the second external electronic device (20b). The number of at least one external electronic device (e.g., the first external electronic device (20a) and / or the second external electronic device (20b)) illustrated in FIG. 1 is merely an example, and embodiments of the present disclosure are not limited thereto.

[0024] In one embodiment of the present disclosure, the electronic device (10) may request data from the first external electronic device (20a). In one example, the electronic device (10) may request data necessary to generate a response to a user input from the first external electronic device (20a). For example, if heart rate data and / or blood pressure data are necessary to generate a response to the user input, the electronic device (10) may request the user's heart rate data and / or blood pressure data from the first external electronic device (20a) (e.g., a smart watch or a smart ring).

[0025] In one embodiment of the present disclosure, the electronic device (10) can receive data requested from a first external electronic device (20a). For example, if the data requested by the electronic device (10) is heart rate data and / or blood pressure data, the electronic device (10) can receive the user's heart rate data and / or blood pressure data measured over a certain period of time from the first external electronic device (20a).

[0026] In one embodiment of the present disclosure, the electronic device (10) can generate information desired by the user using data received from the first external electronic device (20a). In one example, the electronic device (10) can apply a weight to the data received from the first external electronic device (20a). Based on the weighted data, the electronic device (10) can generate information desired by the user. For example, if the user has just finished exercising, the blood pressure is likely to be high, so the electronic device (10) can apply a higher weight to the heart rate data than to the blood pressure data when generating information related to the user's health status. For example, the electronic device (10) can generate information related to the user's health status by applying an 80% weight to the heart rate data and a 20% weight to the blood pressure data.

[0027] In one embodiment of the present disclosure, the electronic device (10) may provide a response including information desired by the user. In one example, the electronic device (10) may generate information desired by the user using received data, and then generate a response including the generated information and provide the response to the user. The electronic device (10) may include in the response the type of data used to generate the information and / or the weight applied to each piece of data. For example, the electronic device (10) may include in the response that the generated information was generated using heart rate data and blood pressure data, and that a weight of 80% was applied to the heart rate data and a weight of 20% was applied to the blood pressure data.

[0028] In one embodiment of the present disclosure, the electronic device (10) can determine the accuracy of the data based on the received data. In one example, the electronic device (10) can determine the accuracy by comparing the data with specified reference information. For example, if a numerical value of the received data falls outside a specified reference range, the electronic device (10) can determine that the accuracy of the data is low. For example, if the signal waveform of the data is not similar to the specified waveform by a certain degree or more, the electronic device (10) can determine that the accuracy of the data is low.

[0029] In one embodiment of the present disclosure, the electronic device (10) can determine a setting value for newly measuring data in the first external electronic device (20a) by judging the accuracy of the received data. For example, the setting value can include at least one of information of a sensor for measuring data, a measurement sensitivity of the sensor for measuring data, or a measurement frequency for measuring data. For example, the electronic device (10) can determine a setting value for turning off a sensor that measures low-accuracy data among the received data or for increasing the measurement sensitivity of the sensor. For example, the electronic device (10) can determine a setting value for increasing the measurement frequency of high-accuracy data among the received data and decreasing the measurement frequency of low-accuracy data.

[0030] In one embodiment of the present disclosure, the electronic device (10) may transmit a command to the first external electronic device (20a) to measure data according to a determined set value. For example, if the electronic device (10) determines that the accuracy of heart rate data is high and the accuracy of blood pressure data is low, the electronic device (10) may transmit a command to the first external electronic device (20a) to increase the measurement frequency of the heart rate data or to increase the sensitivity of a sensor for measuring blood pressure to measure the data. Alternatively, if the accuracy of the blood pressure data is very low (e.g., if the value of the blood pressure data is below a threshold value), the electronic device (10) may transmit a command to the first external electronic device (20a) to turn off the sensor for measuring blood pressure data in order to reduce current consumption.

[0031] In one embodiment of the present disclosure, the electronic device (10) can receive measured data according to a determined setting value from a first external electronic device (20a). The electronic device (10) can receive the measured data according to the determined setting value and generate a response. In one example, the electronic device (10) can apply a weight to the measured data according to the determined setting value. The electronic device (10) can generate information desired by a user by applying a weight to the measured data according to the determined setting value. The electronic device (10) can provide a response including information desired by the user by using the data measured according to the determined setting value.

[0032] In one embodiment of the present disclosure, the electronic device (10) may provide a response including feedback. In one example, if the accuracy of the received data is low, the electronic device (10) may include feedback regarding the wearing position of the first external electronic device (20a) (e.g., a smartwatch) in the response. For example, if the blood pressure value received from the first external electronic device (20a) deviates from the normal range by a certain amount or more, the electronic device (10) may determine that the accuracy of the blood pressure data is low. In order to obtain high-accuracy blood pressure data, the electronic device (10) may provide a response instructing the user to wear the first external electronic device (20a) tightly.

[0033] In one embodiment of the present disclosure, the electronic device (10) may request data from a plurality of external electronic devices (e.g., a first external electronic device (20a), a second external electronic device (20b)). For example, when heart rate data and blood pressure data are required to generate a response to a user input, the electronic device (10) may request the user's heart rate data from the first external electronic device (20a) (e.g., a smart watch, a smart ring) and request the second external electronic device (20b) for blood pressure data.

[0034] In one embodiment of the present disclosure, the electronic device (10) can determine at least one external electronic device from among a plurality of external electronic devices from which to request data. For example, the electronic device (10) can identify at least one external electronic device having a sensor capable of measuring required data from among the plurality of external electronic devices. The electronic device (10) can request the required data from the identified at least one external electronic device. In one example, the electronic device (10) can request two or more external electronic devices to obtain one piece of data. For example, the electronic device (10) can request the user's blood pressure data from a smartwatch and a smart ring to obtain blood pressure data.

[0035] FIG. 2 is a block diagram of a configuration of an electronic device according to one embodiment of the present disclosure.

[0036] In one embodiment of the present disclosure, the electronic device (10) may include a communication circuit (110) (e.g., a communication module (1290) of FIG. 12), at least one camera (e.g., a camera (120), a camera module (1280) of FIG. 12), a display (130) (e.g., a display module (1260) of FIG. 12), at least one sensor (e.g., a sensor (140), a sensor module (1276) of FIG. 12), at least one processor (e.g., a processor (150), a processor (1220) of FIG. 12), a memory (160) (e.g., a memory (1230) of FIG. 12), and / or an AI model (170).

[0037] In one example, the communication circuit (110) may be electrically connected to the processor (150). The communication circuit (110) may transmit and receive data with another electronic device (e.g., the first external electronic device (20a)) using a communication technology. For example, the communication technology may include Bluetooth communication, BLE (Bluetooth Low Energy) communication, near field communication (NFC), WLAN (Wireless Local Area Network) communication, Zigbee communication, Infrared Data Association (IrDA) communication, WFD (Wi-Fi Direct) communication, UWB (Ultra-Wideband) communication, ANT (Advanced and Adaptive Network Technology) communication, WIFI communication, RFID (Radio Frequency Identification) communication, 3G communication, 4G communication, and 5G communication. However, the communication technology is not limited thereto. For example, the communication circuit (110) can transmit and receive data with at least one external electronic device (e.g., a first external electronic device (20a), a second external electronic device (20b)) using any communication protocol. The communication circuit (110) can include at least one circuit for processing a signal. For example, the communication circuit (110) can include at least one converter for frequency modulation of a signal, at least one filter for noise removal of a signal, at least one modem for modulating and / or demodulating a signal, at least one antenna, and / or at least one transceiver.

[0038] In one example, at least one camera (e.g., camera 120) may capture images of the surroundings and / or the interior space of the electronic device (10). For example, the electronic device (10) may include at least one camera configured to acquire images of the surrounding space of the electronic device (10). In one example, the electronic device (10) may include at least one camera configured to acquire images of the front of the electronic device (10) (e.g., the direction in which the eyes of a wearer of the electronic device (10) are directed). The electronic device (10) may acquire parallax information using at least two or more cameras and generate a depth map for the surrounding space based on the parallax information. For example, the electronic device (10) may include at least one internal camera configured to acquire images of a direction toward the wearer of the electronic device (10) (e.g., the direction toward the interior space). Using the internal camera, the electronic device (10) may track the user's gaze. At least one camera may include one or more lenses. For example, at least one camera may include at least one of a standard lens, a wide-angle lens, a telephoto lens, a fisheye lens, a micro lens, or a zoom lens based on a focal length.

[0039] In one example, the display (130) may be configured to generate light of a virtual image. For example, the display (130) may include an optical engine of a projector including an image panel, an illumination optical system, a projection optical system, etc. The display (130) may include a light source that outputs light, an image panel that forms a two-dimensional virtual image using the light output from the light source, and a projection optical system that projects the light of the virtual image formed on the image panel. The light source is an optical component that illuminates light and can generate light by controlling the color of RGB. The light source may be composed of, for example, a light emitting diode (LED). The image panel may be composed of a reflective image panel that modulates light illuminated by the light source into light containing a two-dimensional image and reflects it. The reflective image panel may be, for example, a DMD (Digital Micromirror Device) panel, an LCoS (Liquid Crystal on Silicon) panel, or any other known reflective image panel. The display (130) may be placed on the back of the electronic device (10). The display (130) may be referenced by the display module (1460) of FIG. 14.

[0040] In one example, the processor (150) may be electrically connected to components of the electronic device (10). For example, the processor (150) may be connected to a communication circuit (110), at least one camera, a display (130), at least one sensor, a memory (160), and / or an AI model (170). For example, the processor (150) may be wired to components of the electronic device (10). The processor (150) may be composed of a single chip or multiple chips. For example, the processor (150) may include at least one processing circuitry including a central processing unit (CPU), an application processor (AP), a microprocessor unit (MPU), a communication processor (CP), a system on chip (SoC), and / or an integrated circuit (IC).

[0041] In one example, the memory (160) may include internal memory and / or external memory. For example, the internal memory may include at least one of volatile memory (e.g., dynamic random access memory (DRAM), static random access memory (SRAM), or synchronous DRAM (SDRAM)), nonvolatile memory (e.g., programmable read-only memory (PROM), one time PROM (OTPROM), erasable PROM (EPROM), electrically erasable and PROM (EEPROM), mask ROM, flash ROM, flash memory, a hard drive, or a solid state drive (SSD). The external memory may include at least one of a flash drive (e.g., compact flash), secure digital (SD), micro-SD, mini-SD, extreme digital (xD), multi-media card (MMC), or memory stick.

[0042] In one embodiment of the present disclosure, the AI ​​model (170) may obtain user input for obtaining arbitrary information. For example, the user input may include a user's touch input or voice input for obtaining arbitrary information. For example, the user input may include a user's query for obtaining arbitrary information. For example, the AI ​​model (170) may obtain user input requesting blood pressure information from the user to obtain blood pressure information.

[0043] In one embodiment of the present disclosure, the AI ​​model (170) may determine the level of response including the information based on user information. For example, the user information may include any personal information and / or lifestyle information of the user, such as the user's sleep information, health information, exercise information, and / or diet information. For example, sleep information may include any information related to the user's sleep pattern, such as the user's average sleep start time, wake-up time, and / or total sleep time over a certain period of time. For example, health information may include any information related to the user's health status, such as information about a disease the user has (e.g., diabetes, high blood pressure) and / or medications the user is taking. For example, exercise information may include any information related to the exercise performed by the user, such as the type of exercise performed by the user (e.g., gym, running, swimming), exercise records (e.g., number of deadlifts or squats for gym exercise, distance run or average speed for running), and / or calorie consumption. For example, diet information may include any information related to the food consumed by the user, such as the type of food eaten today, total calories consumed, and time of eating. In one example, if the user input requests blood pressure information, the AI ​​model (170) may determine the level of a response including blood pressure information based on the user information. For example, the AI ​​model (170) may determine the level of a response including blood pressure information as a level indicating whether the blood pressure level is normal. For example, the AI ​​model (170) may determine the level of a response including blood pressure information as a level indicating whether the blood pressure level is high or low. For example, the AI ​​model (170) may determine the level of a response including blood pressure information as a level indicating a specific blood pressure level.In one embodiment of the present disclosure, the AI ​​model (170) can recognize multiple types of data related to the arbitrary information. In one example, the AI ​​model (170) can recognize (or identify) multiple types of data related to the arbitrary information based on the user information. For example, the types of data may include the user's bio-signals, electromyogram signals, and / or movement information. For example, the bio-signals may include at least one of heart rate data, respiration rate information, blood oxygen concentration information, blood pressure data, pulse information, body temperature information, electrocardiogram information, blood flow image information, or body composition analysis information. For example, the movement information may include information related to any movement of the user, such as the distance the user has moved, the number of steps, movement speed, and / or running time.

[0044] In one embodiment of the present disclosure, the AI ​​model (170) may request data corresponding to the recognized types from at least one external electronic device (e.g., a first external electronic device (20a), a second external electronic device (20b)) to provide a determined level of response to the user. For example, if the recognized types of the plurality of data are blood pressure data and heart rate data, the AI ​​model (170) may request the user's blood pressure data and heart rate data from at least one external electronic device. In one example, the AI ​​model (170) may request data corresponding to some of the types of the plurality of data from the first external electronic device (20a), and request data corresponding to the remaining types from the second external electronic device (20b). For example, if the recognized types of the plurality of data are blood pressure data and heart rate data, the AI ​​model (170) may request the user's blood pressure data from the first external electronic device (20a) and request the user's heart rate data from the second external electronic device (20b).

[0045] In one embodiment of the present disclosure, the AI ​​model (170) may receive a plurality of first data from at least one external electronic device. In one example, the AI ​​model (170) may receive data requested by the AI ​​model (170) from at least one external electronic device. For example, if the data requested by the AI ​​model (170) is the user's blood pressure data and heart rate data, the AI ​​model (170) may receive the user's blood pressure data and heart rate data measured over a certain period of time from at least one external electronic device.

[0046] In one embodiment of the present disclosure, the AI ​​model (170) may include information for the user to obtain and provide a response corresponding to the determined level. For example, if the user requests blood pressure information, the AI ​​model (170) may provide a response corresponding to the level of "Your blood pressure is normal (or abnormal)." For example, if the user requests blood pressure information, the AI ​​model (170) may determine a response corresponding to the level of "Your blood pressure is high (or very high, low, or very low)." For example, the AI ​​model (170) may provide a response corresponding to the level of providing the user with a specific blood pressure value.

[0047] In one embodiment of the present disclosure, the AI ​​model (170) may determine a weight for each of the plurality of received first data. In one example, the AI ​​model (170) may determine a weight for each of the plurality of first data based on at least one of the plurality of received first data or user information. For example, the weight may correspond to a parameter value for determining the degree to which each value of the plurality of received first data is reflected. For example, if the AI ​​model (170) receives a user input related to food recommendation and the user's recent exercise was a high-calorie exercise, the AI ​​model (170) may increase the weight of the user's hydration measurement data. For example, if among the plurality of received first data, there is data with a value that falls outside the normal range, the AI ​​model (170) may lower the weight of the data with the value that falls outside the normal range or set it to 0%.

[0048] In one embodiment of the present disclosure, the AI ​​model (170) may apply determined weights to a plurality of first data. The AI ​​model (170) may provide a response including the arbitrary information based on the plurality of first data to which the weights have been applied. In one example, the AI ​​model (170) may generate the arbitrary information by applying weights to the plurality of first data received from at least one external electronic device. For example, if the AI ​​model (170) determines that the weight of data A among the plurality of data is 70% and the weight of data B is 30%, the AI ​​model (170) may generate the arbitrary information by reflecting 70% of data A and 30% of data B.

[0049] In one embodiment of the present disclosure, the AI ​​model (170) may include, in the response provided to the user, the type of data used to generate the arbitrary information and the weight applied to each piece of data. For example, the AI ​​model (170) may include, in the response provided to the user, the content, "The arbitrary information was generated by applying a 70% weight to data A and a 30% weight to data B."

[0050] In one embodiment of the present disclosure, the AI ​​model (170) may include a data measurement guide in the response provided to the user. For example, the data measurement guide may include any feedback that encourages accurate data measurement, such as moving the position of the wearable device the user is wearing, correcting the user's posture, or recommending wearing another wearable device.

[0051] In one embodiment of the present disclosure, the AI ​​model (170) may determine a setting value for measuring data from at least one external electronic device. In one example, the AI ​​model (170) may determine a setting value for measuring data from at least one external electronic device based on user information. For example, the setting value may include at least one of information about a sensor for measuring data, a measurement sensitivity of the sensor for measuring data, or a measurement frequency for measuring data. For example, the AI ​​model (170) may determine a setting value for increasing the frequency of water measurement when the user engages in exercise that burns a lot of calories.

[0052] In one embodiment of the present disclosure, the AI ​​model (170) may determine a set value by determining the accuracy of data. In one example, the AI ​​model (170) may determine the accuracy by comparing the data with specified reference information. For example, if the numerical value of the data falls outside the specified reference range, the AI ​​model (170) may determine that the accuracy of the corresponding data is low. For example, if the signal waveform of the data is not similar to the specified waveform by a certain degree or more, the AI ​​model (170) may determine that the accuracy of the corresponding data is low. In one example, the AI ​​model (170) may determine the accuracy of the data based on information from the external electronic device that transmitted the data or information from the sensor that measured the data. For example, the AI ​​model (170) may determine in advance the accuracy of the data transmitted by the external electronic device based on the type of the external electronic device that transmitted the data. For example, when the AI ​​model (170) receives data on the number of steps from a smart watch and a smart ring, the AI ​​model (170) may determine the accuracy of the data received from the smart watch to be high and the accuracy of the data received from the smart ring to be low based on preset criteria.

[0053] In one embodiment of the present disclosure, the AI ​​model (170) may determine a setting value by judging the accuracy of each of the plurality of received first data. For example, the AI ​​model (170) may determine a setting value to turn off a sensor that measures data with low accuracy among the plurality of received first data or to increase the measurement sensitivity of the sensor. For example, the AI ​​model (170) may determine a setting value to increase the measurement frequency of data with high accuracy among the plurality of received first data and to decrease the measurement frequency of data with low accuracy among the plurality of received first data.

[0054] In one embodiment of the present disclosure, the AI ​​model (170) may transmit a command to at least one external electronic device to measure data based on the determined setpoint. In one example, the AI ​​model (170) may request remeasurement of data related to the arbitrary information based on the determined setpoint. For example, the AI ​​model (170) may transmit a command to at least one external electronic device to increase the measurement frequency of heart rate data and increase the measurement sensitivity of blood pressure data.

[0055] In one embodiment of the present disclosure, the AI ​​model (170) may, in response to the command, receive a plurality of second data from the at least one external electronic device. In one example, the AI ​​model (170) may receive a plurality of second data remeasured according to the determined set value from the at least one external electronic device.

[0056] In one embodiment of the present disclosure, the AI ​​model (170) may provide a response including the arbitrary information based on the received plurality of second data. In one example, the AI ​​model (170) may determine a weight of each of the plurality of second data based on at least one of the received plurality of second data or user information. For example, the method for determining the weight of each of the plurality of second data may be referenced by the method for determining the weight of each of the plurality of first data. In one example, the AI ​​model (170) may generate a response including the arbitrary information using the plurality of second data to which the determined weights have been applied. For example, the method for generating the arbitrary information using the plurality of second data to which the weights have been applied may be referenced by the method for generating the arbitrary information using the plurality of first data to which the weights have been applied.

[0057] In one embodiment of the present disclosure, the AI ​​model (170) may determine at least one external electronic device from among a plurality of external electronic devices to request data necessary for generating the arbitrary information. In one example, the AI ​​model (170) may determine at least one external electronic device from which to request data based on at least one of user information and information related to the plurality of external electronic devices. For example, if the user frequently wears a smartwatch, the AI ​​model (170) may request data from the smartwatch among the plurality of external electronic devices. For example, if the device capable of communicating with the electronic device (10) among the plurality of external electronic devices is a smartwatch, the AI ​​model (170) may request data from the smartwatch.

[0058] In one embodiment of the present disclosure, the AI ​​model (170) may change (e.g., identify) at least one external electronic device from which to request necessary data based on the accuracy of the plurality of first data. In one example, the AI ​​model (170) may add a connection to a new external electronic device from which to request data, or disconnect at least one external electronic device that is currently connected, based on the accuracy of the plurality of first data. For example, the AI ​​model (170) may disconnect an external electronic device that transmitted data with low accuracy among the plurality of first data. The AI ​​model (170) may determine another external electronic device from which to newly measure the data with low accuracy.

[0059] In one embodiment of the present disclosure, the AI ​​model (170) may request data necessary for generating the arbitrary information from the at least one modified external electronic device. The AI ​​model (170) may receive a plurality of second data from the at least one modified external electronic device. Based on the received plurality of second data, the AI ​​model (170) may provide a response including the arbitrary information to the user.

[0060] In one embodiment of the present disclosure, when at least one external electronic device to request data includes two or more external electronic devices, the AI ​​model (170) may determine a priority between the two or more external electronic devices based on the type of the recognized data. In one example, the AI ​​model (170) may determine a priority between the two or more external electronic devices to request data according to a predetermined condition. The AI ​​model (170) may determine a first weight of the plurality of first data based on the determined priority. For example, when the AI ​​model (170) requests data from the first external electronic device (20a) and the second external electronic device (20b) and sets the priority of the first external electronic device (20a) higher than that of the second external electronic device (20b), the AI ​​model (170) may apply a weight of data received from the first external electronic device (20a) to be higher than that of data received from the second external electronic device (20b).

[0061] In one embodiment of the present disclosure, the AI ​​model (170) may determine at least one external electronic device from which to request data based on a user input. In one example, the AI ​​model (170) may determine at least one external electronic device from which to request data in response to a user input according to initially set conditions. The AI ​​model (170) may continuously change the conditions for determining at least one external electronic device from which to request data. For example, the AI ​​model (170) may change the determined at least one external electronic device based on data received from the determined at least one external electronic device. The AI ​​model (170) may also determine the at least one external electronic device based on conditions set by the user. Furthermore, the AI ​​model (170) may change the conditions for determining the at least one external electronic device based on user information. For example, the AI ​​model (170) may change the conditions for determining the at least one external electronic device based on the user's biometric information, location information, or personal information. The AI ​​model (170) can determine data measurement setting values ​​of at least one external electronic device based on the accuracy or measurement sensitivity of data measured by at least one external electronic device.

[0062] In one example, at least one processor may perform operations necessary for the operation of the electronic device (10). Operations of the electronic device (10) (e.g., operations performed by an AI model) may be performed by at least one processor individually or collectively executing instructions. Some of the operations of the electronic device (10) may be performed by a first processor executing instructions, and at least some of the remaining operations may be performed by a processor different from the first processor executing instructions. At least one processor may control components of the electronic device (10). For example, the operations of the electronic device (10) described in the present disclosure may be referenced as being performed by at least one processor. For example, the operations of the electronic device (10) may be performed by at least one processor executing instructions stored in the memory (160).

[0063] In one embodiment of the present disclosure, the memory (160) may store instructions that can be executed by the processor (150). The memory (160) may store at least one piece of data related to the operation of the electronic device (10) or a command related to the functional operation of components of the electronic device (10). For example, the memory (160) may store at least one application that is preloaded upon manufacturing the electronic device (10) or downloaded as a third party from an online market (e.g., an app store). For example, the at least one application may include a voice recognition application that supports the operation of a voice recognition service.

[0064] Each of the components of the electronic device (10) described above may include a single or multiple entities. For example, some of the multiple entities may be separately arranged in other components. In one embodiment, one or more of the components of the electronic device (10) described above may be omitted, or one or more other components may be added. According to one embodiment, the components of the electronic device (10) may omit at least some of the operations of the components of the electronic device (10) described above (e.g., operations of the processor (150)), or may additionally perform one or more other operations.

[0065] FIG. 3 is a block diagram of the configuration of an AI model according to one embodiment of the present disclosure.

[0066] In one embodiment of the present disclosure, an AI model (e.g., AI model (170) of FIG. 2) may include a query type determination module (171) and / or a control module (172).

[0067] In one example, the query type determination module (171) can identify the query type of the user input. For example, the query type may include health, medical, travel, exercise, lifestyle, shopping, cooking, service, finance, economy, and / or education. For example, if the user input is related to “Recommend what to eat for dinner,” the query type determination module (171) can identify the query type of the user input as a cooking type. For example, if the user input is related to “Tell me if I exercised well today,” the query type determination module (171) can identify the query type of the user input as an exercise type.

[0068] In one embodiment of the present disclosure, the control module (172) may include a data analysis and control model (173), a device connection module (174), a question analysis model (175), and / or a feedback control module (176).

[0069] In one example, the data analysis and control model (173) can determine the accuracy of received data. In one example, if the received data falls below a threshold, the data analysis and control model (173) can determine that the accuracy of the data is low. For example, since the normal range of heart rate is 50-100 beats per minute, if the received heart rate data value is approximately 15 beats per minute, the data analysis and control model (173) can determine that the accuracy of the received heart rate data is low. In this case, the threshold may be approximately 20 beats, which is a certain value or more different from the normal range. In one example, the data analysis and control model (173) can determine that the accuracy of the received data is low if the electronic device cannot generate a response with an accuracy higher than a specified value using the received data. For example, the data analysis and control model (173) can determine the level or content of the response desired by the user. The data analysis and control model (173) may determine that the accuracy of the received data is low if the data received from an external electronic device cannot generate a response of the level and / or content desired by the user.

[0070] In one example, the data analysis and control model (173) may determine a weight for each piece of received data based on user information and / or data received from an external electronic device (e.g., the first external electronic device (20a) and the second external electronic device (20b) of FIG. 1). For example, if the user input is related to “How was your workout today?” and the user is diabetic, the data analysis and control model (173) may determine a high weight for data related to blood sugar levels. In one example, the data analysis and control model (173) may determine a weight for each piece of received data based on the accuracy of the received data. For example, the data analysis and control model (173) may determine a high weight for data with high accuracy and a low weight for data with low accuracy.

[0071] In one example, the data analysis and control model (173) may determine a setting value for an external electronic device measuring data based on the accuracy of the data. For example, the data analysis and control model (173) may determine a setting value to increase the measurement frequency of data with high accuracy. For example, the data analysis and control model (173) may determine a setting value to turn off a sensor measuring data with low accuracy or to decrease the measurement frequency. For example, the data analysis and control model (173) may no longer request data from an external electronic device measuring data with low accuracy.

[0072] In one example, the device connection module (174) may determine at least one external electronic device from which to request data based on the results determined by the data analysis and control model (173). For example, the device connection module (174) may request data from an external electronic device with high data accuracy and may no longer request data from an external electronic device with low data accuracy. In one example, the device connection module (174) may determine whether to operate a sensor to measure data based on the results determined by the data analysis and control model (173). For example, the device connection module (174) may continuously operate a sensor that measures high-accuracy data and turn off a sensor that measures low-accuracy data. The device connection module (174) may also change a threshold value that may serve as a criterion for determining the accuracy of data. For example, if the data analysis and control model (173) determines that the accuracy of data received from an external electronic device with high accuracy is low, the device connection module (174) may increase the threshold value. In this case, the data analysis and control model (173) may not determine that the accuracy is low because the numerical value of the received data is no longer less than the threshold value.

[0073] In one example, the device connection module (174) may predetermine at least one external electronic device from which to request data based on the user's usage pattern for the external electronic device. For example, if the user is about to wear the first external electronic device (20a) and the first external electronic device (20a) has a high accuracy for the required data, the device connection module (174) may determine the first external electronic device (20a) as the at least one external electronic device to which to request data. For example, if the user wears the first external electronic device (20a), the device connection module (174) may request the required data from the first external electronic device (20a).

[0074] In one example, the question analysis model (175) can determine the intent of a user input. The question analysis model (175) can determine the sensors required to generate a response to the user input. The question analysis model (175) is normally inactive, but can be activated when the user input differs from existing user input. For example, when a user asks a question that differs from a frequently asked question, the question analysis model (175) can determine the intent of the different question. The question analysis model (175) can identify additional sensor data by determining the intent of the question that differs from the usual question. The question analysis model (175) can request additional sensor data from at least one external electronic device.

[0075] In one example, the question analysis model (175) can determine the intent of a question, which differs from the usual question, based on the user's personal information and / or received data. Based on the intent of the different question, the question analysis model (175) can recommend wearing a specific device. The question analysis model (175) can determine whether a response to user input can be generated based on the accuracy of the received data. The question analysis model (175) can identify factors that should be used to determine accuracy in the data analysis and control model (173).

[0076] In one example, the feedback control module (176) may provide a data measurement guide. For example, the data measurement guide may include any feedback that encourages accurate data measurement, such as moving the position of an external electronic device (e.g., a wearable device) worn by the user, correcting the user's posture, or recommending wearing a different wearable device. For example, the data measurement guide may include a notification to change the weight of currently received data or to wear a new wearable device. For example, if the accuracy of the received data is low, the data measurement guide may provide a notification to wear a different wearable device. For example, the notification may be provided through a user interface (UI).

[0077] FIG. 4 is a flowchart of a method for an electronic device to provide a response corresponding to a user input, according to one embodiment of the present disclosure. In the following, any description that overlaps with the description of FIG. 1 may be omitted or briefly described.

[0078] In operation 410, an electronic device (e.g., the electronic device (10) of FIG. 1) may obtain user input for obtaining information. For example, the user input may include a user's touch input or voice input for obtaining any information. For example, the user input may include a user's query for obtaining any information.

[0079] In operation 420, the electronic device may determine the level of a response including the information. In one example, the electronic device may determine the level of a response including any information (e.g., the degree of detail) based on user information. For example, the user information may include any personal information and / or lifestyle information of the user, such as sleep information, health information, exercise information, and / or diet information. In one example, if the user input requests blood pressure information, the electronic device may determine the level of a response including blood pressure information based on the user information. For example, the electronic device may determine the level of a response including blood pressure information as a level indicating whether the blood pressure level is normal. For example, the electronic device may determine the level of a response including blood pressure information as a level indicating whether the blood pressure level is high or low. For example, the electronic device may determine the level of a response including blood pressure information as a level indicating a specific blood pressure level.

[0080] In operation 430, the electronic device may recognize (e.g., identify) multiple types of data associated with the information. In one example, the electronic device may recognize multiple types of data associated with any information based on user information. For example, the types of data may include the user's bio-signals, electromyogram (EMG) signals, and / or movement information. For example, the bio-signals may include at least one of heart rate data, respiration rate information, blood oxygen concentration information, blood pressure data, pulse information, body temperature information, electrocardiogram (ECG) information, blood flow image information, or body composition analysis information. For example, the movement information may include information associated with any movement of the user, such as the distance the user has moved, the number of steps, the movement speed, and / or the running time.

[0081] In operation 440, the electronic device may request data corresponding to the recognized types from at least one external electronic device (e.g., the first external electronic device (20a) and the second external electronic device (20b) of FIG. 1). For example, if the recognized types of the plurality of data are blood pressure data and heart rate data, the electronic device may request the user's blood pressure data and heart rate data from at least one external electronic device. In one example, the electronic device may request data corresponding to some of the types of the plurality of data from the first external electronic device (20a), and data corresponding to the remaining types from the second external electronic device (20b). For example, if the recognized types of the plurality of data are blood pressure data and heart rate data, the electronic device may request the user's blood pressure data from the first external electronic device (20a), and request the user's heart rate data from the second external electronic device (20b).

[0082] In operation 450, the electronic device may receive multiple pieces of data from at least one external electronic device. In one example, the electronic device may receive data requested from at least one external electronic device from the at least one external electronic device. For example, if the data requested by the electronic device is the user's blood pressure data and heart rate data, the electronic device may receive the user's blood pressure data and heart rate data measured over a certain period of time from at least one external electronic device.

[0083] In operation 460, the electronic device may provide a response that includes the information and corresponds to the determined level. In one example, the electronic device may provide a response that includes information desired by the user based on the user information. For example, the electronic device may provide a response that corresponds to the user's desired level determined in operation 420.

[0084] In one embodiment, when a user requests blood pressure information, the electronic device may provide a response at the level of “Your blood pressure is normal (or abnormal).” For example, if the user’s measured systolic blood pressure is 160 mmHg (or, diastolic blood pressure is 60 mmHg), the user’s blood pressure is not a normal value (e.g., 80 mmHg to 120 mmHg), and therefore, if the level of the response determined in operation 420 is a level indicating whether the blood pressure is normal, the electronic device may provide “Your systolic blood pressure is 160 mmHg, which is not a normal value” (or, “Your diastolic blood pressure is 60 mmHg, which is not a normal value”).

[0085] In one embodiment, when a user requests blood pressure information, the electronic device may determine a response level such as “your blood pressure is high (or very high, low, very low).” to the user. For example, if the user’s measured systolic blood pressure is 160 mmHg (or diastolic blood pressure is 60 mmHg), the user may have high blood pressure (or low blood pressure), and therefore, if the response level determined in operation 420 is a level that indicates whether the blood pressure is high or low, the electronic device may provide “your systolic blood pressure is 160 mmHg, which is higher than the normal value” (or “your diastolic blood pressure is 60 mmHg, which is lower than the normal value”).

[0086] In one embodiment, the electronic device may provide a response at a level that provides a specific blood pressure value to the user. For example, if the user's measured systolic blood pressure value is 160 mmHg (or diastolic blood pressure value is 60 mmHg), the user may have high blood pressure (or low blood pressure), and thus, if the level of the response determined in operation 420 is a level that provides a specific blood pressure value, the electronic device may provide, "The systolic blood pressure is 160 mmHg, which is much higher than the normal value of 120 mmHg" (or, "The diastolic blood pressure is 60 mmHg, which is lower than the normal value of 80 mmHg").

[0087] FIGS. 5A and 5B are diagrams related to an electronic device providing a response based on user information, according to one embodiment of the present disclosure.

[0088] In one embodiment of the present disclosure, an electronic device (500) (e.g., the electronic device (10) of FIG. 1 ) may provide a response corresponding to a user input based on user information. For example, the user information may include the user's health status, information on underlying diseases, and / or health information of interest to the user.

[0089] Referring to FIGS. 5A and 5B , the electronic device (500) provides different responses to two users for the same user input (510, 515). For example, the electronic device (500) may receive the user input (510, 515) “Analyze and let me know if I exercised well today.”

[0090] In FIG. 5A, the first response provision example (501) illustrates an embodiment in which an electronic device (500) provides a response to user 1, who suffers from diabetes and hypertension. In one example, the electronic device (500) may request data from a smartwatch and a smart ring to generate information on whether the user has exercised well. For example, the electronic device (500) may request heart rate data and blood sugar data from the smartwatch and the smart ring.

[0091] In one example, the electronic device (500) may determine a setting value for measuring data based on user information. For example, the electronic device (500) may determine a setting value to increase the data measurement frequency of the smartwatch and decrease the data measurement frequency of the smartring based on the chronic disease information of user 1 suffering from diabetes and hypertension. For example, when the electronic device (500) obtains a user input (510) at time t1, the electronic device (500) may transmit a command to the smartring and the smartwatch to measure data according to the determined setting value. In one example, the electronic device (500) may determine a weight of the data based on the user information. For example, the electronic device (500) may increase the weight of the data of the smartwatch from 50% to 80% and decrease the weight of the data of the smartring from 50% to 20% based on the chronic disease information of user 1 suffering from diabetes and hypertension.

[0092] In one example, referring to graphs (502) and (503), the smart ring and smart watch can measure data according to preset values ​​up to time t1. The smart ring and smart watch can receive a command from the electronic device (500) to measure data according to the determined preset values ​​at time t1. For example, the smart ring can decrease the frequency of data measurement from time t1.

[0093] Referring to the first response provision example (501), the electronic device (500) may include information (520) about the device used for data measurement in the response. For example, the electronic device (500) may include in the response that data was measured using a smartwatch and a smart ring. The electronic device (500) may also include a data measurement guide in the response. For example, the electronic device (500) may include a data measurement guide in the body (530) of the response, which includes a guide for more accurate measurement, such as suggesting a wearing position of the smartwatch.

[0094] In FIG. 5b, the second response provision example (504) illustrates an embodiment in which the electronic device (500) provides a response to User 2, who checks the number of steps taken each day. In one example, the electronic device (500) may request data from the smartwatch and smartring to generate information on whether the user has exercised well. For example, the electronic device (500) may request User 2's calorie consumption data and step count data from the smartwatch and smartring.

[0095] In one example, the electronic device (500) may determine the user's interest information based on user information. For example, the electronic device (500) may determine the user's interest information based on the history of user queries and / or the history of responses provided by the electronic device (500) to the user. In one example, if the user has made the same and / or similar queries a certain number of times or more, the electronic device (500) may determine the user's interest information from the queries. For example, if the user has asked the user how many steps he or she walks every day, the electronic device (500) may determine that checking the number of steps is the user's interest information related to the type of exercise. In one example, if the electronic device (500) has provided the user with responses with the same and / or similar content a certain number of times or more, the electronic device (500) may determine the user's interest information from the responses with the same and / or similar content provided to the user. For example, if the electronic device (500) provides the user with information about the number of steps taken each day in response to a user's query, the electronic device (500) may determine that checking the number of steps is information of interest to the user. In one example, the electronic device (500) may obtain feedback from the user regarding the response provided by the electronic device (500) to the user. In one example, the electronic device (500) may determine the response to provide to the user based on the user's feedback. For example, if the user makes the same and / or similar query, the electronic device (500) may determine the content of the response desired by the user and / or the accuracy associated with the content of the response based on the user's feedback.

[0096] For example, if the electronic device (500) provides a response such as “You walked 6000 steps today” based on a user input such as “How was your walk today?”, the electronic device (500) may receive feedback from the user such as “How was your stride or walking speed?”. The electronic device (500) may provide additional information about the stride or walking speed based on the user’s feedback. When the electronic device (500) obtains the same user input (e.g., “How was your walk today?”) next time, the content of the response desired by the user and / or the degree of accuracy associated with the content of the response may determine that the information is about the stride or walking speed of the user’s steps. For example, when the electronic device (500) obtains the same user input (e.g., “How was your walk today?”) the next time, it may determine that the content of the response desired by the user and / or the degree of accuracy associated with the content of the response is information such as “Today’s walking stride was 70 cm, which was the same as usual, and the cadence was improved by 10%.”

[0097] For example, if the electronic device (500) provides a response such as “You walked 6000 steps today” based on a user input such as “How was your walk today?”, the electronic device (500) may not receive feedback from the user. If the electronic device (500) does not receive feedback from the user, even if it obtains the same user input (e.g., “How was your walk today?”) later, it may determine that the previously provided response (e.g., “You walked 6000 steps today”) is the content of the response desired by the user and / or the degree of accuracy associated with the content of the response.

[0098] For example, if the electronic device (500) provides a response such as “I finished 2 km in 15 minutes today” based on a user input such as “How was your run today?”, the electronic device (500) may receive feedback from the user such as “Was your stride or running speed okay?”. The electronic device (500) may provide additional information about the stride or running speed based on the user’s feedback. When the electronic device (500) obtains the same user input (e.g., “How was your run today?”) next time, the content of the response desired by the user and / or the degree of accuracy associated with the content of the response may determine that the content of the response is information about the user’s stride or walking speed for running. For example, when the electronic device (500) obtains the same user input (e.g., “How was your run today?”) the next time, it may determine that the information such as “Today’s run, my stride was a little narrower than usual at 100 cm, and my cadence improved by 10%” is the content of the response desired by the user and / or the degree of accuracy associated with the content of the response.

[0099] For example, if the electronic device (500) provides a response such as “I finished 2 km in 15 minutes today” based on a user input such as “How was your running today?”, the electronic device (500) may not receive feedback from the user. If the electronic device (500) does not receive feedback from the user, even if it obtains the same user input (e.g., “How was your running today?”) later, it may determine that the previously provided response (e.g., “I finished 2 km in 15 minutes today”) is the content of the response desired by the user and / or the degree of accuracy associated with the content of the response.

[0100] In one example, the electronic device (500) may determine a setting value for measuring data based on user information or accuracy. For example, the electronic device (500) may determine a setting value to increase the data measurement frequency of the smart ring and to stop the data measurement of the smart watch based on the interest information of user 2 who checks the number of steps every day. For example, the electronic device (500) may determine a setting value to stop the measurement of data with low accuracy when the accuracy of the received data is low (e.g., when the data value is lower than a threshold value). For example, when the electronic device (500) obtains a user input (515) at time t1, the electronic device (500) may transmit a command to the smart ring and the smart watch to measure data according to the determined setting value. In one example, the electronic device (500) may determine a weighting of the data based on user information or accuracy. For example, the electronic device (500) may increase the weight of data from the smart ring from 50% to 100% and decrease the weight of data from the smart watch from 50% to 0% based on the interest information of user 2 who checks the number of steps every day. For example, the electronic device (500) may lower the weight or set it to 0% if the numerical accuracy of the received data is low.

[0101] In one example, referring to graph (505) and graph (506), the smart ring and the smart watch can measure data according to preset values ​​up to time t1. The smart ring and the smart watch can receive a command from the electronic device (500) to measure data according to the determined preset values ​​at time t1. For example, the smart ring can increase the frequency of data measurement from time t1, and the smart watch can stop measuring data. For example, since the numerical value of the data measured by the smart watch up to time t1 is less than the threshold value d4, the smart watch can receive a command from the electronic device (500) to stop measuring data.

[0102] Referring to the second response provision example (504), the electronic device (500) may include information (525) about the device used to measure data in the response. For example, the electronic device (500) may include in the response that data was measured using a smart ring. The electronic device (500) may provide feedback to the user in the body (535) of the response to the user input. For example, the electronic device (500) may include feedback such as “Please maintain the same amount of exercise as now” in the body (535) of the response.

[0103] FIGS. 6A and 6B are diagrams showing data measured by an external electronic device in the form of graphs according to one embodiment of the present disclosure.

[0104] According to one embodiment, an electronic device (e.g., the electronic device (10) of FIG. 1) may provide different responses to the same user input based on user information. In one example, if the query type of the user input (e.g., the query type described above in FIG. 3) is a type related to diet, the electronic device may identify information about the user's recent exercise records stored in the electronic device. For example, the electronic device may identify information about the exercise records (e.g., exercise type, number of exercise sessions, exercise frequency, exercise time) performed by the user over a recent period (e.g., one week, one month). For example, the electronic device may obtain the user's recent exercise records through an exercise-related application. In one example, if the query type of the user input is a type related to diet, the electronic device may identify information about the user's recent exercise records and generate a response to the user input. In one example, after providing the response generated based on the user information, the electronic device may change the setting values ​​of a preset external electronic device. For example, the setting values ​​of the external electronic device may correspond to the conditions under which the external electronic device (e.g., the first external electronic device (20a) and the second external electronic device (20b) of FIG. 1) measures data.

[0105] According to one embodiment, after providing a response generated based on user information, the electronic device may change the setting value of a preset external electronic device to obtain information associated with the response. For example, the electronic device may provide different responses based on user information for the same user input, and then change the setting value of the preset external electronic device to a different value. Hereinafter, in FIGS. 6A and 6B , an embodiment is described in which the electronic device provides different responses to two users for the same user input, and then changes the setting value of a preset external electronic device (e.g., a smart ring or a smart watch) to a different value at time t1.

[0106] In one example, referring to FIGS. 6A and 6B , the electronic device may provide different responses to two users (e.g., a first user and a second user) at time t1 for the same user input, and then change the preset setting values ​​of the external electronic device differently. For example, if the user input is “Recommend my menu for today,” the electronic device may change the setting values ​​for the external electronic device to measure data based on the user’s recent exercise information. For example, the first user may be a user who has recently performed daily health exercise, and the second user may be a user who has recently performed daily swimming exercise.

[0107] In one example, graphs (601) and (602) of FIG. 6A are graphs representing heart rate data of a first user measured through a smart ring and a smart watch, in order for the electronic device to obtain the blood flow of the first user (a user who has recently performed daily health exercise). For example, time t1 may correspond to the time at which the electronic device receives a user input. For example, since a smart watch has higher accuracy than a smart ring in measuring heart rate, the smart ring may not measure the heart rate of the first user until a user input is received (e.g., before time t1) according to a preset setting value, and the smart watch may measure the heart rate of the first user. For example, if the user input of the first user is “Recommend me a menu for today,” the electronic device may receive the heart rate measured through the smart watch until time t1. The electronic device may obtain the blood flow using the heart rate of the first user. Based on the blood flow, the electronic device may generate a response related to the diet. After providing a response, the electronic device can change the settings of the smart ring and smart watch to more closely examine the changes in blood flow. For example, the electronic device can transmit a command to the smart ring to measure heart rate. For example, the electronic device can transmit a command to the smart watch to increase the frequency of measuring heart rate. For example, the smart ring can measure heart rate starting from time t1. For example, the smart watch can increase the frequency of measuring heart rate starting from time t1. Referring to graphs (601) and (602), the heart rate data values ​​received through the smart ring and smart watch can exceed thresholds (d1, d2), respectively. In one example, the electronic device can change the settings to increase the measurement sensitivity if the heart rate data values ​​received from the smart ring and / or smart watch are lower than the thresholds.

[0108] In one example, graphs (603) and (604) of FIG. 6B are graphs representing data on the body fluid content of a second user measured through a smart ring and a smart watch, in order for the electronic device to obtain the body fluid content of the second user (a user who has recently performed daily swimming exercise). For example, time t1 may correspond to the time at which the electronic device receives a user input. For example, since a smart watch is more accurate than a smart ring in measuring body fluid content, the smart ring may not measure the body fluid content of the second user until a user input is received (e.g., before time t1) according to a preset setting, and the smart watch may measure the body fluid content of the second user. For example, if the user input of the second user is “Recommend me a menu for today,” the electronic device may receive the body fluid content measured through the smart watch until time t1. Based on the body fluid content of the second user, the electronic device may generate a response related to the diet. After providing a response, the electronic device can change the settings of the smart ring and smart watch to more specifically monitor changes in body water content. For example, the electronic device can transmit a command to the smart ring to measure body water content. For example, the smart ring can measure body water content starting from time t1. For example, the electronic device can transmit a command to the smart watch to increase the frequency of body water content measurement. For example, the smart watch can increase the frequency of body water content measurement starting from time t1. In one example, if the body water content data value received through the smart watch before time t1 is less than a threshold value (d4), the electronic device can transmit a command to the smart watch to increase the measurement sensitivity. For example, the body water content data value measured through the smart watch starting from time t1 may be greater than the threshold value (d4).

[0109] FIG. 7 is a flowchart illustrating a method for an electronic device to provide a response to a user input according to an embodiment of the present disclosure. In the following, any description that overlaps with the description of FIG. 4 may be omitted or briefly described.

[0110] In operation 705, an electronic device (e.g., the electronic device (10) of FIG. 1) may obtain a user input for obtaining any information. For example, the user input may include a user's touch input or voice input for obtaining any information. For example, the user input may include a user's query for obtaining any information.

[0111] In operation 710, the electronic device may determine whether the user input is a question corresponding to an AI model classification. In one example, the electronic device may identify the query type of the user input using an AI model (e.g., the AI ​​model (70) of FIG. 2). If the identified query type of the user input does not correspond to a query type included in a query type determination module (e.g., the query type determination module (171) of FIG. 3), the electronic device may determine that the user input is not a question corresponding to an AI model classification. If it is determined that the user input is not a question corresponding to an AI model classification (e.g., operation 710-No), the electronic device may provide a response using existing information in operation 715. For example, in operation 715, the electronic device may provide a response to the user input using previously learned information.

[0112] In one example, if the type of query of the identified user input corresponds to a type of query included in the query type determination module, the electronic device may determine that the user input is a question corresponding to the AI ​​model classification. If it is determined that the user input is a question corresponding to the AI ​​model classification (e.g., operation 710-Yes), in operation 720, the electronic device may determine at least one external electronic device from which to request data. For example, the electronic device may determine at least one external electronic device from which to request data based on at least one of user information or information related to a plurality of external electronic devices. For example, if the user frequently wears a smartwatch, the electronic device may request data from the smartwatch among the plurality of external electronic devices. For example, if a device capable of communicating with the electronic device among the plurality of external electronic devices is a smartwatch, the electronic device may request data from the smartwatch. In one example, the electronic device may determine the level or content of a response desired by the user. The electronic device may determine at least one external electronic device from which to request data necessary for generating the response based on the level and / or content of the response determined from the external electronic device. In one example, the electronic device may determine at least one external electronic device from which to request data based on the accuracy of the response to be provided to the user. For example, if the electronic device seeks to provide a response with an accuracy higher than a specified value, the electronic device may request data necessary to generate the response from multiple external electronic devices. For example, if the electronic device seeks to provide a response with an accuracy higher than a specified value, the electronic device may request the necessary data from the external electronic device that measures the data necessary to generate the response with the highest accuracy.For example, if an electronic device is to provide a response with a specified accuracy, the electronic device may request the necessary data from an external electronic device that consumes the least amount of current and / or data. In operation 725, the electronic device may receive a plurality of first data from at least one external electronic device that requested the data.

[0113] In operation 730, the electronic device may determine whether the determined at least one external electronic device should be replaced. In one example, the electronic device may determine whether the determined at least one external electronic device should be replaced based on the accuracy of the plurality of received first data. For example, if the accuracy of the plurality of received first data is low, the electronic device may determine that the determined at least one external electronic device should be replaced. In one example, if the electronic device cannot generate a response of a level and / or content desired by the user using the plurality of received first data, the electronic device may determine that the accuracy of the plurality of first data is low. In one example, if the numerical value of the plurality of received first data is lower than a specified threshold, the electronic device may determine that the accuracy of the plurality of first data is low.

[0114] If it is determined that at least one of the determined external electronic devices needs to be changed (e.g., operation 730-Yes), the electronic device may determine whether to change the weights in operation 735. In one example, the electronic device may determine whether to change the weights based on the accuracy of the plurality of received first data. For example, if there is data with low accuracy among the plurality of received first data, the electronic device may need to change the weights by lowering the weights of the data with low accuracy and increasing the weights of the other data.

[0115] If the electronic device determines that the weights do not need to be changed (e.g., operation 735-No), the electronic device may perform operation 725. For example, if the electronic device determines that the weights do not need to be changed, the electronic device may continue to receive data measured according to the existing set values ​​from the at least one external electronic device determined above.

[0116] If the electronic device determines that the weights need to be changed (e.g., operation 735 - Yes), then in operation 740, the electronic device may change at least one of the determined external electronic devices. For example, if the electronic device wants to change the weight of low-accuracy data to 0%, the electronic device may stop requesting data from the external electronic device that transmitted the low-accuracy data. If the electronic device changes the determined at least one external electronic device, the electronic device may perform operation 725. For example, the electronic device may receive data from the changed at least one external electronic device.

[0117] If it is determined that at least one of the determined external electronic devices does not need to be changed (e.g., operation 730-No), then in operation 745, the electronic device may determine whether there is a connection history with another external electronic device that assists in generating the response. For example, the other external electronic device that assists in generating the response may include an external electronic device that can accurately measure data required to generate the response. For example, the connection history may include a history of the electronic device receiving data from another external electronic device.

[0118] If there is a connection history with another external electronic device that is helpful in generating a response (e.g., operation 745-Yes), in operation 755, the electronic device may provide a notification based on the frequency of use of the other external electronic device. In one example, if there is a connection history with the other external electronic device, the electronic device may identify the frequency of use of the other external electronic device. Based on the frequency of use of the other external electronic device, the electronic device may provide a notification suggesting wearing the other external electronic device. For example, if the user does not plan to use the other external electronic device for the time being based on the frequency of use, the electronic device may provide a notification including a suggestion to wear the other external electronic device. For example, if the user plans to wear the other external electronic device soon based on the frequency of use, the electronic device may not provide a separate notification.

[0119] If the electronic device provides a notification based on the frequency of use of the other external electronic device, the electronic device may perform operation 740. For example, if the notification includes a suggestion to wear the other external electronic device, the electronic device may change at least one external electronic device to include the other external electronic device. For example, even if the user is expected to wear the other external electronic device soon based on the frequency of use, the electronic device may change at least one external electronic device to include the other external electronic device.

[0120] If there is no history of connection with another external electronic device that would assist in generating a response (e.g., operation 745-No), then in operation 750, the electronic device may provide feedback related to the other external electronic device. For example, the electronic device may provide feedback indicating that it can provide more accurate information if the other external electronic device is worn. For example, the feedback may include information about the other external electronic device (e.g., device type).

[0121] FIG. 8 is a signal flow diagram between an electronic device and at least one external electronic device, for providing a response to a user input, according to one embodiment of the present disclosure. In the following, any description overlapping with that of FIG. 4 or 7 may be omitted or briefly described.

[0122] In operation 805, the electronic device (800) (e.g., the electronic device (10) of FIG. 1) may determine at least one external electronic device (801) (e.g., the first external electronic device (20a) and the first external electronic device (20b) of FIG. 1) based on a user input. For example, the electronic device (800) may identify data required for a response to the user input. The electronic device (800) may determine at least one external electronic device (801) from which to request the identified data.

[0123] In operation 810, the electronic device (800) may transmit a signal including a sensor setting and a data request to at least one external electronic device (801). For example, the electronic device (800) may transmit a sensor setting value for measuring the identified data to at least one external electronic device (801). For example, the electronic device (800) may request the identified data from at least one external electronic device (801).

[0124] In operation 815, at least one external electronic device (801) may transmit sensor data. For example, at least one external electronic device (801) may measure data according to a sensor setting value received from the electronic device (800). At least one external electronic device (801) may transmit sensor data measuring data requested by the electronic device (800) to the electronic device (800). For example, the sensor data may correspond to data measuring a user's heart rate through a heart rate sensor.

[0125] In operation 820, at least one external electronic device (801) may transmit data related to at least one external electronic device (801) to an AI model of the electronic device (800) (e.g., the AI ​​model (170) of FIG. 2). For example, the data related to at least one external electronic device (801) may include battery level information of the at least one external electronic device (801) itself, battery level information of a sensor, and / or communication status information.

[0126] In operation 825, the electronic device (800) may change the determined at least one external electronic device using the AI ​​model (170). For example, the AI ​​model (170) may change the determined at least one external electronic device based on received sensor data and / or data related to the at least one external electronic device. For example, the AI ​​model (170) may stop requesting data from an external electronic device having a remaining battery level below a specified standard among the at least one external electronic device (801). For example, if there is a sensor among the sensors of the at least one external electronic device (801) having a remaining battery level below a specified standard, the AI ​​model (170) may stop data measurement through the sensor.

[0127] In operation 830, the electronic device (800) may determine a setting value for data measurement using the AI ​​model (170). For example, the AI ​​model (170) may change the setting value of the sensor transmitted in operation 810. For example, the AI ​​model (170) may determine a setting value for data measurement based on user information, received sensor data, and / or data related to at least one external electronic device (801).

[0128] In operation 835, the electronic device (800) may transmit a command to at least one external electronic device (801) to measure data according to the determined set value. For example, the electronic device (800) may transmit a command to at least one external electronic device (801) to measure data by changing the measurement frequency of specific data or changing the measurement sensitivity of a specific sensor.

[0129] In operation 840, at least one external electronic device (801) may transmit measured sensor data to the electronic device (800) according to the determined setting value. For example, at least one external electronic device (801) may change the measurement frequency of specific data or change the measurement sensitivity of a specific sensor to transmit the measured data to the electronic device (800).

[0130] In operation 845, the electronic device (800) may provide a response to the user input. For example, the electronic device (800) may include in the response the type of data used to generate the response, the weight of the data, and / or the type of at least one external electronic device (801). For example, the electronic device (800) may include in the response feedback recommending wearing another external electronic device. For example, the electronic device (800) may provide a response that includes a data measurement guide for more accurate data measurement.

[0131] FIG. 9 is a signal flow diagram between an electronic device and multiple external electronic devices, for providing a response to a user input, according to one embodiment of the present disclosure. In the following, any descriptions that overlap with those of FIG. 4, 7, or 8 may be omitted or briefly described.

[0132] In steps 905, 910, and 915, the electronic device (900) (e.g., the electronic device (10) of FIG. 1) may perform wireless communication with a plurality of external electronic devices (e.g., the first external electronic device (901), the second external electronic device (902), the third external electronic device (903), the first external electronic device (20a), the second external electronic device (20b) of FIG. 1). For example, the electronic device (900) may transmit and receive data through wireless communication with the plurality of external electronic devices to generate a response to a user input. For example, the electronic device (900) may perform wireless communication with the plurality of external electronic devices using Bluetooth communication technology and / or UWB communication technology.

[0133] In steps 920, 925, and 930, the plurality of external electronic devices may transmit sensor data to an AI model (990) of the electronic device (900) (e.g., the AI ​​model (170) of FIG. 2 ). For example, the plurality of external electronic devices may request data necessary for generating a response from the electronic device (900). For example, the plurality of external electronic devices may transmit sensor data measuring the requested data to the AI ​​model (990). For example, the plurality of external electronic devices may measure data according to initially set configuration values.

[0134] In operations 935, 940, and 945, the electronic device (900) may maintain or release a connection with a plurality of external electronic devices. For example, the device connection module (991) of the electronic device (900) (e.g., the device connection module (174) of FIG. 3 ) may determine an external electronic device to maintain or release a connection with. For example, the AI ​​model (990) may change at least some of the plurality of external electronic devices based on received sensor data, user information, and / or user input. If at least some of the plurality of external electronic devices are changed, the device connection module (991) may transmit a signal to each of the plurality of external electronic devices to maintain or release a communication connection. Operations 935, 940, and 945 may be referenced by operations 825 to 835 of FIG. 8 .

[0135] In operations 950, 955, and 960, a plurality of external electronic devices may transmit sensor data to a data analysis model (992) of the electronic device (900) (e.g., the data analysis and control model (173) of FIG. 3 ). In FIG. 9 , the first external electronic device (901), the second external electronic device (902), and the third external electronic device (903) are all illustrated as transmitting sensor data in operations 950, 955, and 960, but external electronic devices that are disconnected from the electronic device (900) in operations 935 to 945 may not transmit sensor data.

[0136] In steps 965, 970, and 975, the electronic device (900) may maintain or disconnect connections with a plurality of external electronic devices. For example, the data analysis model (992) of the electronic device (900) may determine which external electronic devices to maintain or disconnect. For example, the data analysis model (992) may modify at least some of the plurality of external electronic devices based on received sensor data, user information, and / or user input.

[0137] FIG. 10 is a diagram illustrating a method for an electronic device to change a data measurement setting value of an external electronic device according to one embodiment of the present disclosure.

[0138] In one embodiment of the present disclosure, an electronic device (1010) (e.g., the electronic device (10) of FIG. 1) may obtain a user input. The electronic device may use an AI model (e.g., the AI ​​model (170) of FIG. 2) to determine at least one external electronic device (1020, 1030) (e.g., a first external electronic device (1020) (e.g., the first external electronic device (20a)), a second external electronic device (20b)) (e.g., a smart watch, a smart ring)) from which to request data. For example, referring to FIG. 10, the electronic device may request data from a smart watch and a smart ring.

[0139] In one embodiment of the present disclosure, an electronic device may receive data measured from a smartwatch and a smart ring up to time t1. The electronic device may determine the accuracy of the received data using a data analysis and control model (e.g., the data analysis and control model (173) of FIG. 3). For example, referring to the graph of FIG. 10, since the numerical value of the data measured by the smartwatch up to time t1 is less than a threshold value d2, the data analysis and control model may determine that the accuracy of the smartwatch is low. In one example, the data analysis and control model may determine the level or content of a response desired by a user. If the data analysis and control model cannot generate a response of the level and / or content desired by the user using the data received from the external electronic device, the accuracy of the received data may be determined to be low. If the data analysis and control model can generate a response of the level and / or content desired by the user using the data received from the external electronic device, the accuracy of the received data may be determined to be high.

[0140] In one embodiment of the present disclosure, the data analysis model may change the setting value for measuring data based on the accuracy of the received data. For example, the data analysis model may change the setting value to stop data measurement by the smartwatch and increase the data measurement frequency of the smart ring because the accuracy of the smartwatch is low. In one example, the data analysis model may change the weight of the data based on the accuracy of the received data. For example, if the weight of the data measured by the smartwatch is initially set higher than the weight of the data measured by the smart ring, the data analysis model may change the weight of the data measured by the smartwatch to 0% or lower than the weight of the data measured by the smart ring because the accuracy of the smartwatch is low. For example, referring to FIG. 10, at time t1, the electronic device may transmit a command to the smartwatch and the smart ring to measure data according to the setting value changed by the data analysis model. For example, the smartwatch may turn off the sensor measuring the data after time t1. For example, a smart ring could increase the frequency of data measurements after time t1.

[0141] FIG. 11 is a diagram illustrating an electronic device determining a weight of data based on a user's usage pattern for multiple external electronic devices, according to one embodiment of the present disclosure.

[0142] Referring to FIG. 11, an electronic device (e.g., the electronic device (10) of FIG. 1) may determine weights for data measured by multiple external electronic devices based on a user's usage pattern for the multiple external electronic devices. For example, if a user slept until time t1, the electronic device may determine the weight of data measured by the smart ring to be 100% based on the user's usage pattern of wearing only a smart ring during sleeping hours. For example, if a user wore a smart watch at time t3 after waking up, the electronic device may determine the weight of data measured by the smart watch to be 70% and reduce the weight of data measured by the smart ring from 100% to 30%. For example, if the user takes off the smartwatch and puts on the smart earphones at time t4, the electronic device can determine the weight of the data measured by the smartwatch as 0%, the weight of the data measured by the smart earphones as 10%, and increase the weight of the data measured by the smart ring from 30% to 90%.

[0143] In one embodiment of the present disclosure, an electronic device may include a graph indicating the weighting of data by time zone in its response to the user. The electronic device may include feedback in the response recommending the wearing of another electronic device. For example, the electronic device may include in the response that wearing the other external electronic device may increase accuracy by a certain percentage.

[0144] Although FIG. 11 illustrates that data weighting is determined based on a user's usage pattern (e.g., usage time) for multiple external electronic devices, the present invention is not limited thereto. For example, the electronic device may determine data weighting based on information related to multiple external electronic devices (e.g., battery level, communication status), measured data accuracy, measurement sensitivity, user information, and / or user input.

[0145] According to one embodiment of the present disclosure, an electronic device (10, 500, 800, 900, 1201) may include a communication circuit (110), a memory (160, 1230) for storing instructions, and at least one processor (150, 1220).

[0146] According to one embodiment of the present disclosure, the instructions, when executed by the at least one processor, may cause the electronic device to obtain user input for obtaining information.

[0147] According to one embodiment of the present disclosure, the instructions, when executed by the at least one processor, may cause the electronic device to determine, based on user information, a level of response including the information.

[0148] According to one embodiment of the present disclosure, the instructions, when executed by the at least one processor, may cause the electronic device to recognize a plurality of types of data related to the user information, at least in part based on the user information.

[0149] According to one embodiment of the present disclosure, the instructions, when executed by the at least one processor, may cause the electronic device to request data corresponding to the recognized type from at least one external electronic device (20a, 20b, 801, 901, 902, 903, 1204).

[0150] According to one embodiment of the present disclosure, the instructions, when executed by the at least one processor, may cause the electronic device to receive at least one first data from the at least one external electronic device based on the request.

[0151] According to one embodiment of the present disclosure, the instructions, when executed by the at least one processor, may cause the electronic device to provide a response including the information and corresponding to the determined level, based on the received at least one first data.

[0152] According to one embodiment of the present disclosure, the at least one first data may include a plurality of first data.

[0153] According to one embodiment of the present disclosure, the instructions, when executed by the at least one processor, may cause the electronic device to determine a first weight of each of the plurality of first data based on at least one of the plurality of first data or the user information.

[0154] According to one embodiment of the present disclosure, the instructions, when executed by the at least one processor, may cause the electronic device to provide a response including the information corresponding to the determined level by applying the determined first weight to the plurality of first data.

[0155] According to one embodiment of the present disclosure, the instructions, when executed by the at least one processor, may cause the electronic device to determine a setting value for measuring data corresponding to the recognized type in the at least one external electronic device based on at least one of the plurality of first data or the user information.

[0156] According to one embodiment of the present disclosure, the instructions, when executed by the at least one processor, may cause the electronic device to transmit a command to the at least one external electronic device to measure data corresponding to the recognized type using the determined setting value.

[0157] According to one embodiment of the present disclosure, the instructions, when executed by the at least one processor, may cause the electronic device to receive at least one second data from the at least one external electronic device in response to the instructions.

[0158] According to one embodiment of the present disclosure, the instructions, when executed by the at least one processor, may cause the electronic device to provide a response including the information corresponding to the determined level based on the at least one second data.

[0159] According to one embodiment of the present disclosure, the at least one second data may include a plurality of second data.

[0160] According to one embodiment of the present disclosure, the instructions, when executed by the at least one processor, may cause the electronic device to determine a second weight of each of the plurality of second data based on at least one of the plurality of second data or the user information.

[0161] According to one embodiment of the present disclosure, the instructions, when executed by the at least one processor, may cause the electronic device to provide a response including the information corresponding to the determined level by applying the determined second weight to the plurality of second data.

[0162] According to one embodiment of the present disclosure, the setting value may include at least one of information of a sensor for measuring data corresponding to the recognized type, measurement sensitivity of a sensor for measuring data corresponding to the recognized type, or measurement frequency for measuring data corresponding to the recognized type.

[0163] According to one embodiment of the present disclosure, the instructions, when executed by the at least one processor, may cause the electronic device to determine the accuracy of each of the plurality of first data based on a result of comparing each of the plurality of first data with specified reference information.

[0164] According to one embodiment of the present disclosure, the instructions, when executed by the at least one processor, may cause the electronic device to determine at least one of the first weight or the set value based at least in part on the accuracy.

[0165] According to one embodiment of the present disclosure, the instructions, when executed by the at least one processor, may cause the electronic device to determine the accuracy of each of the plurality of first data based on at least one of information of the at least one external electronic device that provided the plurality of first data or information of a sensor that measured the plurality of first data.

[0166] According to one embodiment of the present disclosure, the instructions, when executed by the at least one processor, may cause the electronic device to determine at least one of the first weight or the set value based at least in part on the accuracy.

[0167] According to one embodiment of the present disclosure, the instructions, when executed by the at least one processor, may cause the electronic device to determine, based on at least one of the user information or information associated with the plurality of different external electronic devices, the at least one external electronic device to which the request should be transmitted among the plurality of different external electronic devices.

[0168] According to one embodiment of the present disclosure, the instructions, when executed by the at least one processor, may cause the electronic device to determine the accuracy of each of the plurality of first data based on a result of comparing each of the plurality of first data with specified reference information.

[0169] According to one embodiment of the present disclosure, the instructions, when executed by the at least one processor, may cause the electronic device to change the at least one external electronic device to which the request is to be transmitted, based at least in part on the accuracy.

[0170] According to one embodiment of the present disclosure, the instructions, when executed by the at least one processor, may cause the electronic device to transmit the request to the at least one external electronic device that has been modified.

[0171] According to one embodiment of the present disclosure, the instructions, when executed by the at least one processor, may cause the electronic device to receive a plurality of second data from the at least one changed external electronic device based on the request.

[0172] According to one embodiment of the present disclosure, the instructions, when executed by the at least one processor, may cause the electronic device to provide a response including the information corresponding to the determined level based on the plurality of second data.

[0173] According to one embodiment of the present disclosure, the instructions, when executed by the at least one processor, may cause the electronic device to determine the accuracy of each of the plurality of first data based on at least one of information of the at least one external electronic device that provided the plurality of first data or information of a sensor that measured the plurality of first data.

[0174] According to one embodiment of the present disclosure, the instructions, when executed by the at least one processor, may cause the electronic device to change the at least one external electronic device to which the request is to be transmitted, based at least in part on the accuracy.

[0175] According to one embodiment of the present disclosure, the instructions, when executed by the at least one processor, may cause the electronic device to transmit the request to the at least one external electronic device that has been modified.

[0176] According to one embodiment of the present disclosure, the instructions, when executed by the at least one processor, may cause the electronic device to receive a plurality of second data from the at least one changed external electronic device based on the request.

[0177] According to one embodiment of the present disclosure, the instructions, when executed by the at least one processor, may cause the electronic device to provide a response including the information corresponding to the determined level based on the plurality of second data.

[0178] According to one embodiment of the present disclosure, the instructions, when executed by the at least one processor, may cause the electronic device to determine a priority between the two or more external electronic devices based on a type of the recognized data, if the determined at least one external electronic device includes two or more external electronic devices.

[0179] According to one embodiment of the present disclosure, the instructions, when executed by the at least one processor, may cause the electronic device to determine the first weight based on the priority.

[0180] According to one embodiment of the present disclosure, the instructions, when executed by the at least one processor, may cause the electronic device to provide a data measurement guide to a user for providing a response including the information corresponding to the determined level based on at least one of the plurality of first data, the user input, or information associated with the at least one external electronic device.

[0181] According to one embodiment of the present disclosure, the instructions, when executed by the at least one processor, may cause the electronic device to determine a level of a response including the information based on at least one of a history of user input related to the information, a history of responses of the electronic device related to the information, or user feedback regarding responses of the electronic device related to the information.

[0182] According to one embodiment of the present disclosure, a method for providing a response to a user input of an electronic device may include an operation of obtaining a user input for obtaining information.

[0183] According to one embodiment of the present disclosure, a method for providing a response to a user input of an electronic device may include an operation of determining a level of a response including the information based on user information.

[0184] According to one embodiment of the present disclosure, a method of providing a response to a user input of an electronic device may include an operation of recognizing, at least in part, types of data related to user information.

[0185] According to one embodiment of the present disclosure, a method of providing a response to a user input of an electronic device may include requesting data corresponding to the recognized type from at least one external electronic device.

[0186] According to one embodiment of the present disclosure, a method for providing a response to a user input of an electronic device may include receiving at least one first data from at least one external electronic device based on the request.

[0187] According to one embodiment of the present disclosure, a method of providing a response to a user input of an electronic device may include providing a response including the information and corresponding to the determined level, based on the at least one first data received.

[0188] According to one embodiment of the present disclosure, the at least one first data may include a plurality of first data.

[0189] According to one embodiment of the present disclosure, a method for providing a response to a user input of an electronic device may include an operation of determining a first weight of each of the plurality of first data based on at least one of the plurality of first data or the user information.

[0190] According to one embodiment of the present disclosure, a method of providing a response to a user input of an electronic device may include an operation of applying the determined first weight to the plurality of first data to provide a response including the information corresponding to the determined level.

[0191] According to one embodiment of the present disclosure, a method for providing a response to a user input of an electronic device may include an operation of determining a setting value for measuring data corresponding to the recognized type in the at least one external electronic device based on at least one of the plurality of first data or the user information.

[0192] According to one embodiment of the present disclosure, a method of providing a response to a user input of an electronic device may include an operation of transmitting a command to the at least one external electronic device to measure data corresponding to the recognized type using the determined setting value.

[0193] According to one embodiment of the present disclosure, a method of providing a response to a user input of an electronic device may include receiving, in response to the command, at least one second data from the at least one external electronic device.

[0194] According to one embodiment of the present disclosure, a method for providing a response to a user input of an electronic device may include providing a response corresponding to the determined level based on the at least one second data.

[0195] According to one embodiment of the present disclosure, the at least one second data may include a plurality of second data.

[0196] According to one embodiment of the present disclosure, a method of providing a response to a user input of an electronic device may include an operation of determining a second weight of each of the plurality of second data based on at least one of the plurality of second data or the user information.

[0197] According to one embodiment of the present disclosure, the operation of providing a response including the information corresponding to the determined level may include an operation of providing a response including the information corresponding to the determined level by applying the determined second weight to the plurality of second data.

[0198] According to one embodiment of the present disclosure, the setting value may include at least one of information of a sensor for measuring data corresponding to the recognized type, measurement sensitivity of a sensor for measuring data corresponding to the recognized type, or measurement frequency for measuring data corresponding to the recognized type.

[0199] According to one embodiment of the present disclosure, the operation of determining the first weight or the operation of determining the set value may include an operation of determining the accuracy of each of the plurality of first data based on a result of comparing each of the plurality of first data with specified reference information.

[0200] According to one embodiment of the present disclosure, the operation of determining the first weight or the operation of determining the set value may include an operation of determining at least one of the first weight or the set value based at least in part on the accuracy.

[0201] According to one embodiment of the present disclosure, the operation of determining the first weight or the operation of determining the set value may include an operation of determining the accuracy of each of the plurality of first data based on at least one of information of the at least one external electronic device that provided the plurality of first data or information of a sensor that measured the plurality of first data.

[0202] According to one embodiment of the present disclosure, the operation of determining the first weight or the operation of determining the set value may include an operation of determining at least one of the first weight or the set value based at least in part on the accuracy.

[0203] According to one embodiment of the present disclosure, the operation of providing a response including the information corresponding to the determined level may include an operation of determining at least one external electronic device to which the request is to be transmitted among the plurality of different external electronic devices based on at least one of the user information or information associated with the plurality of different external electronic devices.

[0204] According to one embodiment of the present disclosure, the operation of providing a response including the information corresponding to the determined level may include an operation of determining the accuracy of each of the plurality of first data based on a result of comparing each of the plurality of first data with specified reference information.

[0205] According to one embodiment of the present disclosure, the action of providing a response including the information corresponding to the determined level may include an action of changing the at least one external electronic device to which the request is to be transmitted, based at least in part on the accuracy.

[0206] According to one embodiment of the present disclosure, the action of providing a response including the information corresponding to the determined level may include the action of transmitting the request to the at least one external electronic device that has been changed.

[0207] According to one embodiment of the present disclosure, the operation of providing a response including the information corresponding to the determined level may include an operation of receiving at least one second data from the at least one changed external electronic device based on the request.

[0208] According to one embodiment of the present disclosure, the operation of providing a response including the information corresponding to the determined level may include an operation of providing a response including the information corresponding to the determined level based on the at least one second data.

[0209] In one embodiment of the present disclosure, a computer-readable storage medium can store instructions.

[0210] In one embodiment of the present disclosure, the instructions, when executed by at least one processor, may cause the at least one processor to obtain user input for obtaining information.

[0211] In one embodiment of the present disclosure, the instructions, when executed by at least one processor, may cause the at least one processor to recognize, at least in part, types of data associated with the user information.

[0212] In one embodiment of the present disclosure, the instructions, when executed by at least one processor, may cause the at least one processor to request data corresponding to the recognized type from at least one external electronic device.

[0213] In one embodiment of the present disclosure, the instructions, when executed by at least one processor, may cause the at least one processor to receive a plurality of first data from the at least one external electronic device based on the request.

[0214] In one embodiment of the present disclosure, the instructions, when executed by at least one processor, may cause the at least one processor to determine a first weight of each of the plurality of first data based on at least one of the plurality of first data or the user information.

[0215] In one embodiment of the present disclosure, the instructions, when executed by at least one processor, may cause the at least one processor to apply the determined first weight to the plurality of first data to provide a response including the information corresponding to the determined level.

[0216] FIG. 12 is a block diagram of an electronic device (1201) within a network environment (1200), according to various embodiments.

[0217] Referring to FIG. 12, in a network environment (1200), an electronic device (1201) may communicate with an electronic device (1202) via a first network (1298) (e.g., a short-range wireless communication network), or may communicate with at least one of an electronic device (1204) or a server (1208) via a second network (1299) (e.g., a long-range wireless communication network). According to one embodiment, the electronic device (1201) may communicate with the electronic device (1204) via the server (1208). According to one embodiment, the electronic device (1201) may include a processor (1220), a memory (1230), an input module (1250), an audio output module (1255), a display module (1260), an audio module (1270), a sensor module (1276), an interface (1277), a connection terminal (1278), a haptic module (1279), a camera module (1280), a power management module (1288), a battery (1289), a communication module (1290), a subscriber identification module (1296), or an antenna module (1297). In some embodiments, the electronic device (1201) may omit at least one of these components (e.g., the connection terminal (1278)), or may have one or more other components added. In some embodiments, some of these components (e.g., sensor module (1276), camera module (1280), or antenna module (1297)) may be integrated into a single component (e.g., display module (1260)).

[0218] The processor (1220) may control at least one other component (e.g., a hardware or software component) of the electronic device (1201) connected to the processor (1220) by executing, for example, software (e.g., a program (1240)), and may perform various data processing or operations. According to one embodiment, as at least a part of the data processing or operations, the processor (1220) may store commands or data received from other components (e.g., a sensor module (1276) or a communication module (1290)) in a volatile memory (1232), process the commands or data stored in the volatile memory (1232), and store result data in a non-volatile memory (1234). According to one embodiment, the processor (1220) may include a main processor (1221) (e.g., a central processing unit or an application processor) or a secondary processor (1223) (e.g., a graphics processing unit, a neural processing unit (NPU), an image signal processor, a sensor hub processor, or a communication processor) that can operate independently or together with the main processor (1221). For example, when the electronic device (1201) includes the main processor (1221) and the secondary processor (1223), the secondary processor (1223) may be configured to use less power than the main processor (1221) or to be specialized for a given function. The secondary processor (1223) may be implemented separately from the main processor (1221) or as a part thereof.

[0219] The auxiliary processor (1223) may control at least a portion of functions or states associated with at least one component (e.g., the display module (1260), the sensor module (1276), or the communication module (1290)) of the electronic device (1201), for example, on behalf of the main processor (1221) while the main processor (1221) is in an inactive (e.g., sleep) state, or together with the main processor (1221) while the main processor (1221) is in an active (e.g., application execution) state. In one embodiment, the auxiliary processor (1223) (e.g., an image signal processor or a communication processor) may be implemented as a part of another functionally related component (e.g., a camera module (1280) or a communication module (1290)). In one embodiment, the auxiliary processor (1223) (e.g., a neural network processing unit) may include a hardware structure specialized for processing artificial intelligence models. The artificial intelligence models may be generated through machine learning. This learning can be performed, for example, on the electronic device (1201) itself where the artificial intelligence model is executed, or can be performed through a separate server (e.g., server (1208)). The learning algorithm can include, for example, supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning, but is not limited to the examples described above. The artificial intelligence model can include multiple artificial neural network layers.The artificial neural network may be one of a deep neural network (DNN), a convolutional neural network (CNN), a recurrent neural network (RNN), a restricted Boltzmann machine (RBM), a deep belief network (DBN), a bidirectional recurrent deep neural network (BRDNN), a deep Q-network, or a combination of two or more of the above, but is not limited to the examples described above. In addition to, or alternatively to, a hardware structure, an artificial intelligence model may include a software structure.

[0220] The memory (1230) can store various data used by at least one component (e.g., the processor (1220) or the sensor module (1276)) of the electronic device (1201). The data can include, for example, software (e.g., the program (1240)) and input data or output data for commands related thereto. The memory (1230) can include a volatile memory (1232) or a non-volatile memory (1234).

[0221] The program (1240) may be stored as software in memory (1230) and may include, for example, an operating system (1242), middleware (1244), or an application (1246).

[0222] The input module (1250) can receive commands or data to be used in a component of the electronic device (1201) (e.g., a processor (1220)) from an external source (e.g., a user) of the electronic device (1201). The input module (1250) can include, for example, a microphone, a mouse, a keyboard, a key (e.g., a button), or a digital pen (e.g., a stylus pen).

[0223] The audio output module (1255) can output audio signals to the outside of the electronic device (1201). The audio output module (1255) can include, for example, a speaker or a receiver. The speaker can be used for general purposes, such as multimedia playback or recording playback. The receiver can be used to receive incoming calls. In one embodiment, the receiver can be implemented separately from the speaker or as part of the speaker.

[0224] The display module (1260) can visually provide information to an external party (e.g., a user) of the electronic device (1201). The display module (1260) may include, for example, a display, a holographic device, or a projector and a control circuit for controlling the device. In one embodiment, the display module (1260) may include a touch sensor configured to detect a touch, or a pressure sensor configured to measure the intensity of a force generated by the touch.

[0225] The audio module (1270) can convert sound into an electrical signal, or vice versa, convert an electrical signal into sound. According to one embodiment, the audio module (1270) can acquire sound through the input module (1250), output sound through the sound output module (1255), or an external electronic device (e.g., electronic device (1202)) (e.g., speaker or headphone) directly or wirelessly connected to the electronic device (1201).

[0226] The sensor module (1276) can detect the operating status (e.g., power or temperature) of the electronic device (1201) or the external environmental status (e.g., user status) and generate an electrical signal or data value corresponding to the detected status. According to one embodiment, the sensor module (1276) can include, for example, a gesture sensor, a gyro sensor, a barometric pressure sensor, a magnetic sensor, an acceleration sensor, a grip sensor, a proximity sensor, a color sensor, an IR (infrared) sensor, a biometric sensor, a temperature sensor, a humidity sensor, or an illuminance sensor.

[0227] The interface (1277) may support one or more designated protocols that may be used to directly or wirelessly connect the electronic device (1201) with an external electronic device (e.g., the electronic device (1202)). In one embodiment, the interface (1277) may include, for example, a high definition multimedia interface (HDMI), a universal serial bus (USB) interface, an SD card interface, or an audio interface.

[0228] The connection terminal (1278) may include a connector through which the electronic device (1201) may be physically connected to an external electronic device (e.g., the electronic device (1202)). According to one embodiment, the connection terminal (1278) may include, for example, an HDMI connector, a USB connector, an SD card connector, or an audio connector (e.g., a headphone connector).

[0229] The haptic module (1279) can convert electrical signals into mechanical stimuli (e.g., vibration or movement) or electrical stimuli that a user can perceive through tactile or kinesthetic sensations. In one embodiment, the haptic module (1279) can include, for example, a motor, a piezoelectric element, or an electrical stimulation device.

[0230] The camera module (1280) can capture still images and videos. According to one embodiment, the camera module (1280) may include one or more lenses, image sensors, image signal processors, or flashes.

[0231] The power management module (1288) can manage power supplied to the electronic device (1201). According to one embodiment, the power management module (1288) can be implemented, for example, as at least a part of a power management integrated circuit (PMIC).

[0232] A battery (1289) may power at least one component of the electronic device (1201). In one embodiment, the battery (1289) may include, for example, a non-rechargeable primary battery, a rechargeable secondary battery, or a fuel cell.

[0233] The communication module (1290) may support the establishment of a direct (e.g., wired) communication channel or a wireless communication channel between the electronic device (1201) and an external electronic device (e.g., electronic device (1202), electronic device (1204), or server (1208)), and the performance of communication through the established communication channel. The communication module (1290) may operate independently from the processor (1220) (e.g., application processor) and may include one or more communication processors that support direct (e.g., wired) communication or wireless communication. According to one embodiment, the communication module (1290) may include a wireless communication module (1292) (e.g., a cellular communication module, a short-range wireless communication module, or a global navigation satellite system (GNSS) communication module) or a wired communication module (1294) (e.g., a local area network (LAN) communication module, or a power line communication module). Any of these communication modules may communicate with an external electronic device (1204) via a first network (1298) (e.g., a short-range communication network such as Bluetooth, wireless fidelity (WiFi) direct, or infrared data association (IrDA)) or a second network (1299) (e.g., a long-range communication network such as a legacy cellular network, a 5G network, a next-generation communication network, the Internet, or a computer network (e.g., a LAN or WAN)). These various types of communication modules may be integrated into a single component (e.g., a single chip) or implemented as multiple separate components (e.g., multiple chips). The wireless communication module (1292) may use subscriber information (e.g., an international mobile subscriber identity (IMSI)) stored in the subscriber identification module (1296) to verify or authenticate the electronic device (1201) within a communication network such as the first network (1298) or the second network (1299).

[0234] The wireless communication module (1292) can support 5G networks and next-generation communication technologies following the 4G network, such as NR access technology (new radio access technology). The NR access technology can support high-speed transmission of high-capacity data (eMBB (enhanced mobile broadband)), minimization of terminal power and connection of multiple terminals (mMTC (massive machine type communications)), or high reliability and low latency (URLLC (ultra-reliable and low-latency communications)). The wireless communication module (1292) can support, for example, a high-frequency band (e.g., mmWave band) to achieve a high data transmission rate. The wireless communication module (1292) can support various technologies for securing performance in high-frequency bands, such as beamforming, massive multiple-input and multiple-output (MIMO), full dimensional MIMO (FD-MIMO), array antenna, analog beam-forming, or large scale antenna. The wireless communication module (1292) can support various requirements specified in the electronic device (1201), an external electronic device (e.g., the electronic device (1204)), or a network system (e.g., the second network (1299)). According to one embodiment, the wireless communication module (1292) may support a peak data rate (e.g., 20 Gbps or more) for eMBB realization, a loss coverage (e.g., 164 dB or less) for mMTC realization, or a U-plane latency (e.g., 0.5 ms or less for downlink (DL) and uplink (UL), or 1 ms or less for round trip) for URLLC realization.

[0235] The antenna module (1297) can transmit or receive signals or power to or from an external device (e.g., an external electronic device). In one embodiment, the antenna module (1297) may include an antenna including a radiator formed of a conductor or a conductive pattern formed on a substrate (e.g., a PCB). In one embodiment, the antenna module (1297) may include a plurality of antennas (e.g., an array antenna). In this case, at least one antenna suitable for a communication method used in a communication network, such as the first network (1298) or the second network (1299), may be selected from the plurality of antennas by, for example, the communication module (1290). A signal or power may be transmitted or received between the communication module (1290) and the external electronic device via the at least one selected antenna. In some embodiments, in addition to the radiator, another component (e.g., a radio frequency integrated circuit (RFIC)) may be additionally formed as a part of the antenna module (1297).

[0236] According to various embodiments, the antenna module (1297) may form a mmWave antenna module. According to one embodiment, the mmWave antenna module may include a printed circuit board, an RFIC disposed on or adjacent a first side (e.g., a bottom side) of the printed circuit board and capable of supporting a designated high frequency band (e.g., a mmWave band), and a plurality of antennas (e.g., an array antenna) disposed on or adjacent a second side (e.g., a top side or a side side) of the printed circuit board and capable of transmitting or receiving signals in the designated high frequency band.

[0237] At least some of the above components can be interconnected and exchange signals (e.g., commands or data) with each other via a communication method between peripheral devices (e.g., a bus, GPIO (general purpose input and output), SPI (serial peripheral interface), or MIPI (mobile industry processor interface)).

[0238] According to one embodiment, commands or data may be transmitted or received between the electronic device (1201) and an external electronic device (1204) via a server (1208) connected to a second network (1299). Each of the external electronic devices (1202 or 1204) may be the same or a different type of device as the electronic device (1201). According to one embodiment, all or part of the operations executed in the electronic device (1201) may be executed in one or more of the external electronic devices (1202, 1204, or 1208). For example, when the electronic device (1201) is to perform a certain function or service automatically or in response to a request from a user or another device, the electronic device (1201) may, instead of or in addition to executing the function or service itself, request one or more external electronic devices to perform the function or at least a part of the service. One or more external electronic devices that receive the request may execute at least a portion of the requested function or service, or an additional function or service related to the request, and transmit the result of the execution to the electronic device (1201). The electronic device (1201) may process the result as is or additionally and provide it as at least a portion of a response to the request. For this purpose, cloud computing, distributed computing, mobile edge computing (MEC), or client-server computing technology may be used, for example. The electronic device (1201) may provide an ultra-low latency service using, for example, distributed computing or mobile edge computing. In another embodiment, the external electronic device (1204) may include an Internet of Things (IoT) device. The server (1208) may be an intelligent server utilizing machine learning and / or a neural network.In one embodiment, an external electronic device (1204) or server (1208) may be included in the second network (1299). The electronic device (1201) may be applied to intelligent services (e.g., smart homes, smart cities, smart cars, or healthcare) based on 5G communication technology and IoT-related technology.

[0239] Electronic devices according to the various embodiments disclosed in this document may take various forms. Electronic devices may include, for example, portable communication devices (e.g., smartphones), computer devices, portable multimedia devices, portable medical devices, cameras, wearable devices, or home appliances. Electronic devices according to the embodiments of this document are not limited to the aforementioned devices.

[0240] The various embodiments of this document and the terminology used therein are not intended to limit the technical features described in this document to specific embodiments, but should be understood to include various modifications, equivalents, or substitutes of the embodiments. In connection with the description of the drawings, similar reference numerals may be used for similar or related components. The singular form of a noun corresponding to an item may include one or more of the items, unless the context clearly indicates otherwise. In this document, each of the phrases "A or B", "at least one of A and B", "at least one of A or B", "A, B, or C", "at least one of A, B, and C", and "at least one of A, B, or C" can include any one of the items listed together in the corresponding phrase among those phrases, or all possible combinations thereof. Terms such as "first," "second," or "first" or "second" may be used merely to distinguish one component from another, and do not limit the components in any other respect (e.g., importance or order). When a component (e.g., a first component) is referred to as "coupled" or "connected" to another component (e.g., a second component), with or without the terms "functionally" or "communicatively," it means that the component can be connected to the other component directly (e.g., wired), wirelessly, or through a third component.

[0241] The term "module" used in various embodiments of this document may include a unit implemented in hardware, software, or firmware, and may be used interchangeably with terms such as logic, logic block, component, or circuit. A module may be an integral component, or a minimum unit or part of such a component that performs one or more functions. For example, according to one embodiment, a module may be implemented in the form of an application-specific integrated circuit (ASIC).

[0242] Various embodiments of the present document may be implemented as software (e.g., a program (1240)) including one or more instructions stored in a storage medium (e.g., an internal memory (1236) or an external memory (1238)) readable by a machine (e.g., an electronic device (1201)). For example, a processor (e.g., a processor (1220)) of the machine (e.g., an electronic device (1201)) may call at least one instruction among the one or more instructions stored from the storage medium and execute it. This enables the machine to operate to perform at least one function according to the at least one called instruction. The one or more instructions may include code generated by a compiler or code executable by an interpreter. The machine-readable storage medium may be provided in the form of a non-transitory storage medium. Here, 'non-transitory' simply means that the storage medium is a tangible device and does not contain signals (e.g., electromagnetic waves), and the term does not distinguish between cases where data is stored semi-permanently or temporarily on the storage medium.

[0243] According to one embodiment, the method according to various embodiments disclosed in the present document may be provided as included in a computer program product. The computer program product may be traded as a product between a seller and a buyer. The computer program product may be distributed in the form of a machine-readable storage medium (e.g., compact disc read-only memory (CD-ROM)), or may be distributed online (e.g., downloaded or uploaded) via an application store (e.g., Play Store™) or directly between two user devices (e.g., smart phones). In the case of online distribution, at least a portion of the computer program product may be temporarily stored or temporarily generated in a machine-readable storage medium, such as the memory of a manufacturer's server, an application store's server, or an intermediary server.

[0244] According to various embodiments, each component (e.g., a module or a program) of the above-described components may include one or more entities, and some of the entities may be separated and placed in other components. According to various embodiments, one or more components or operations of the aforementioned components may be omitted, or one or more other components or operations may be added. Alternatively or additionally, a plurality of components (e.g., a module or a program) may be integrated into a single component. In such a case, the integrated component may perform one or more functions of each of the plurality of components identically or similarly to those performed by the corresponding component among the plurality of components prior to the integration. According to various embodiments, the operations performed by a module, program, or other component may be executed sequentially, in parallel, iteratively, or heuristically, or one or more of the operations may be executed in a different order, omitted, or one or more other operations may be added.

Claims

1. In electronic devices, communication circuit; Memory that stores instructions; and comprising at least one processor; The above instructions, when executed by the at least one processor, cause the electronic device to: Obtain user input to obtain information, Based on the user information, determine the level of response that includes the information, Based at least in part on the user information, identifying a plurality of types of data related to the information, Transmitting a request to at least one external electronic device for requesting data corresponding to the plurality of data types identified above, Based on the above request, receiving at least one first data from the at least one external electronic device, Based on the first data, provide a response including the information corresponding to the determined level, An electronic device, wherein the user information includes at least one of a history of user input related to the information, a history of responses of the electronic device related to the information, or user feedback regarding responses of the electronic device related to the information.

2. In claim 1, The at least one first data includes a plurality of first data, The above instructions, when executed by the at least one processor, cause the electronic device to: Based on at least one of the plurality of first data or the user information, a first weight of each of the plurality of first data is determined, An electronic device that applies the determined first weight to the plurality of first data to provide a response including the information corresponding to the determined level.

3. In claim 1, The above instructions, when executed by the at least one processor, cause the electronic device to: Based on at least one of the first data or at least one of the user information, determining a setting value for measuring data corresponding to the plurality of data types in the at least one external electronic device, Using the determined setting value, a command is transmitted to at least one external electronic device to measure data corresponding to the recognized type, In response to the above command, receiving at least one second data from the at least one external electronic device; An electronic device, further comprising: providing a response including the information corresponding to the determined level, based on at least one of the second data.

4. In claim 3, The at least one second data includes a plurality of second data, The above instructions, when executed by the at least one processor, cause the electronic device to: Based on at least one of the plurality of second data or the user information, a second weight of each of the plurality of second data is determined, An electronic device that applies the determined second weight to the plurality of second data to provide a response including the information corresponding to the determined level.

5. In claim 3, An electronic device, wherein the setting value includes at least one of information of a sensor for measuring data corresponding to the identified plurality of data types, measurement sensitivity of a sensor for measuring data corresponding to the identified plurality of data types, or measurement frequency for measuring data corresponding to the identified plurality of data types.

6. In claim 1 or 2, The above instructions, when executed by the at least one processor, cause the electronic device to: Based on information of the at least one external electronic device that provided the at least one first data, information of a sensor that measured the at least one first data, or a result of comparing each of the at least one first data with specified reference information, the accuracy of each of the at least one first data is determined, An electronic device for determining the first weight based at least in part on the accuracy.

7. In any one of claims 3 to 5, The above instructions, when executed by the at least one processor, cause the electronic device to: Based on at least one of information of the at least one external electronic device that provided the at least one first data, information of a sensor that measured the at least one first data, or a result of comparing each of the at least one first data with specified reference information, the accuracy of each of the at least one first data is determined, An electronic device that determines the set value based at least in part on the accuracy.

8. In claim 1, The above instructions, when executed by the at least one processor, cause the electronic device to: An electronic device that determines at least one external electronic device to which the request will be transmitted among the plurality of external electronic devices based on at least one of the user information or information related to the plurality of external electronic devices.

9. In claim 8, The above instructions, when executed by the at least one processor, cause the electronic device to: Based on the result of comparing each of the at least one first data with the specified reference information, the accuracy of each of the at least one first data is determined, Based at least in part on the accuracy, identifying at least one external electronic device other than the at least one external electronic device to which the request is to be transmitted among the plurality of external electronic devices; transmitting said request to said at least one other external electronic device; Based on the above request, receiving at least one second data from the at least one other external electronic device, An electronic device, further comprising: providing a response including the information corresponding to the determined level, based on at least one of the second data.

10. In claim 8, The above instructions, when executed by the at least one processor, cause the electronic device to: Based on at least one of information of the at least one external electronic device that provided the at least one first data or information of a sensor that measured the at least one first data, the accuracy of each of the at least one first data is determined, Based at least in part on the accuracy, identifying at least one external electronic device other than the at least one external electronic device to which the request is to be transmitted among the plurality of external electronic devices; transmitting said request to said at least one other external electronic device; Based on the above request, receiving at least one second data from the at least one other external electronic device, An electronic device, further comprising: providing a response including the information corresponding to the determined level, based on at least one of the second data.

11. In claim 8, The above instructions, when executed by the at least one processor, cause the electronic device to: If the at least one external electronic device includes two or more external electronic devices, a priority is determined between the two or more external electronic devices based on the types of the identified plurality of data, An electronic device that determines a second weight for the at least one second data based on the above priority.

12. In claim 1, The above instructions, when executed by the at least one processor, cause the electronic device to: An electronic device that provides a user with a data measurement guide for providing a response including the information corresponding to the level based on at least one of the at least one first data, the user input, or information related to the at least one external electronic device.

13. A method for providing a response to a user input of an electronic device, An action to obtain user input to obtain information; An action to determine the level of response including said information based on user information; An action of identifying a plurality of types of data related to said information, based at least in part on said user information; An action of transmitting a request to at least one external electronic device requesting data corresponding to the plurality of data types identified above; Based on the request, an operation of receiving at least one first data from the at least one external electronic device; and An operation for providing a response including the information corresponding to the determined level based on at least one first data received above, A method wherein the user information comprises at least one of a history of user input related to the information, a history of responses of the electronic device related to the information, or user feedback regarding responses of the electronic device related to the information.

14. In claim 13, The at least one first data includes a plurality of first data, An operation of determining a first weight of each of the plurality of first data based on at least one of the plurality of first data or the user information; A method comprising an operation of providing a response including the information corresponding to the determined level by applying the determined first weight to the plurality of first data.

15. In claim 13, A method further comprising an action of determining at least one external electronic device to which the request will be transmitted among the plurality of external electronic devices based on at least one of the user information or information related to the plurality of external electronic devices.

Images