Electronic device and non-transitory computer-readable storage medium for identifying spot for wireless communication on basis of image

Abstract

This electronic device may comprise: a camera; a display; a communication circuit for Wireless Fidelity (Wi-Fi); a processor; and a memory storing instructions. The instructions, when executed by the processor, may instruct the electronic device to: acquire, through the camera, image data for an image to be displayed through the display on the basis of an event for using Wi-Fi; by using the image data, identify candidate spots for using Wi-Fi within a place associated with the event; identify at least one recommended spot from among the candidate spots on the basis of the respective locations of the candidate spots; and display the at least one recommended spot so as to be visually emphasized compared to at least one remaining candidate spot among the candidate spots in order to guide access to a radio access node device in the at least one recommended spot.

Description

Electronic device for identifying spots for wireless communication based on images and non-transient computer-readable storage medium

[0001] The following descriptions relate to an electronic device for identifying a spot for wireless communication based on an image and a non-transient computer-readable storage medium.

[0002] A user's electronic device capable of communicating with external electronic devices (e.g., smartphones and head-wearable electronic devices) may be connected to an access point (AP) or a base station by the user. For example, the AP and the base station may allow the electronic device to access a wireless network by enabling the connection between the wireless network and the electronic device.

[0003] The information described above may be provided as related art for the purpose of aiding understanding of the present disclosure. No claim or determination is made as to whether any of the foregoing may be applied as prior art related to the present disclosure.

[0004] An electronic device is provided. The electronic device may include a camera, a display, at least one processor including a communication circuit for wireless fidelity (Wi-Fi) and a processing circuit, and a memory including one or more storage media for storing instructions. The instructions may cause the electronic device to identify an event for the use of Wi-Fi when executed individually or collectively by the at least one processor. The instructions may cause the electronic device to acquire image data through the camera for an image to be displayed through the display based on the event when executed individually or collectively by the at least one processor. The instructions may cause the electronic device to display the image through the display when executed individually or collectively by the at least one processor. The above instructions, when executed individually or collectively by the at least one processor, may cause the electronic device to identify candidate spots for Wi-Fi use within the location associated with the event using the image data. The above instructions, when executed individually or collectively by the at least one processor, may cause the electronic device to receive wireless communication signals from a wireless access node device around the electronic device. The above instructions, when executed individually or collectively by the at least one processor, may cause the electronic device to identify the location of each of the candidate spots defined for the wireless access node device and the electronic device using the wireless communication signals and the image data.The above instructions may cause the electronic device to identify at least one recommended spot among the candidate spots based on the location of each of the candidate spots when executed individually or collectively by the at least one processor. The above instructions may cause the electronic device to display the at least one recommended spot within the image displayed through the display, with the at least one recommended spot visually highlighted relative to the remaining candidate spot among the candidate spots, in order to guide access to the wireless access node device at the at least one recommended spot when executed individually or collectively by the at least one processor.

[0005] A non-transient computer-readable storage medium is provided. The non-transient computer-readable storage medium may store one or more programs. The one or more programs may be executed by an electronic device having a camera, a display, and a communication circuit for Wi-Fi (wireless fidelity). The one or more programs may include instructions that cause the electronic device to identify an event for the use of Wi-Fi when executed by the electronic device. The one or more programs may include instructions that cause the electronic device to acquire image data for an image to be displayed through the display, based on the event, through the camera when executed by the electronic device. The one or more programs may include instructions that cause the electronic device to display the image through the display when executed by the electronic device. The one or more programs mentioned above may include instructions that cause the electronic device to identify candidate spots for Wi-Fi use within the location associated with the event using the image data when executed by the electronic device. The one or more programs mentioned above may include instructions that cause the electronic device to receive wireless communication signals from a wireless access node device around the electronic device when executed by the electronic device. The one or more programs mentioned above may include instructions that cause the electronic device to identify the location of each of the candidate spots defined for the wireless access node device and the electronic device using the wireless communication signals and the image data when executed by the electronic device.The above one or more programs may include instructions that cause the electronic device to identify at least one recommended spot among the candidate spots based on the location of each of the candidate spots when executed by the electronic device. The above one or more programs may include instructions that cause the electronic device to display the at least one recommended spot within the image displayed through the display, with the at least one recommended spot visually highlighted relative to at least one remaining candidate spot among the candidate spots, in order to guide access to the wireless access node device at the at least one recommended spot when executed by the electronic device.

[0006] An electronic device is provided. The electronic device may include at least one processor comprising a camera, a communication circuit for Wi-Fi (wireless fidelity), and a processing circuit, and a memory comprising one or more storage media for storing instructions. The instructions may cause the electronic device to identify an event for Wi-Fi use when executed individually or collectively by the at least one processor. The instructions may cause the electronic device to acquire image data through the camera based on the event when executed individually or collectively by the at least one processor. The instructions may cause the electronic device to identify candidate spots for Wi-Fi use within a location associated with the event using the image data when executed individually or collectively by the at least one processor. The above instructions, when executed individually or collectively by the at least one processor, may cause the electronic device to receive wireless communication signals from a wireless access node device around the electronic device. The above instructions, when executed individually or collectively by the at least one processor, may cause the electronic device to identify the location of each of the candidate spots defined for the wireless access node device and the electronic device using the wireless communication signals and the image data. The above instructions, when executed individually or collectively by the at least one processor, may cause the electronic device to determine the estimated throughputs when accessing the wireless access node device at each of the candidate spots based on the location of each of the candidate spots.The above instructions may cause the electronic device to identify at least one recommended spot among the candidate spots based on at least a portion of the estimated throughputs when executed individually or collectively by the at least one processor. The above instructions may cause the electronic device to provide information about the at least one recommended spot to guide access to the wireless access node device at the at least one recommended spot when executed individually or collectively by the at least one processor.

[0007] A non-transient computer-readable storage medium is provided. The non-transient computer-readable storage medium may store one or more programs. The one or more programs may be executed by an electronic device having a communication circuit for a camera and Wi-Fi (wireless fidelity). The one or more programs may include instructions that cause the electronic device to identify an event for Wi-Fi use when executed by the electronic device. The one or more programs may include instructions that cause the electronic device to acquire image data through the camera based on the event when executed by the electronic device. The one or more programs may include instructions that cause the electronic device to identify candidate spots for Wi-Fi use within a location associated with the event using the image data when executed by the electronic device. The above one or more programs may include instructions that cause the electronic device to receive wireless communication signals from a wireless access node device around the electronic device when executed by the electronic device. The above one or more programs may include instructions that cause the electronic device to identify the location of each of the candidate spots defined for the wireless access node device and the electronic device using the wireless communication signals and the image data when executed by the electronic device. The above one or more programs may include instructions that cause the electronic device to determine the estimated throughputs when accessing the wireless access node device at each of the candidate spots based on the location of each of the candidate spots when executed by the electronic device.The one or more programs may include instructions that cause the electronic device to identify at least one recommended spot among the candidate spots based on at least a portion of the estimated throughputs when executed by the electronic device. The one or more programs may include instructions that cause the electronic device to provide information about the at least one recommended spot to guide access to the wireless access node device at the at least one recommended spot when executed by the electronic device.

[0008] An electronic device is provided. The electronic device may include at least one processor comprising a wireless communication circuit, a camera, and a processing circuit, and a memory comprising one or more storage media for storing instructions. When the instructions are executed individually or collectively by the at least one processor, the electronic device may be caused to obtain first information corresponding to a wireless access node device located within a wireless communication range with the electronic device via the wireless communication circuit. When the instructions are executed individually or collectively by the at least one processor, the electronic device may be caused to obtain second information corresponding to a candidate spot near the electronic device based at least partially on an image corresponding to the surroundings of the electronic device obtained through the camera. When the instructions are executed individually or collectively by the at least one processor, the electronic device may be caused to estimate the predicted communication quality for the wireless access node device at the candidate spot based at least partially on the first information and the second information. The above instructions, when executed individually or collectively by the at least one processor, may cause the electronic device to provide third information corresponding to a recommended spot for performing wireless communication through the wireless access node device, based at least in part on the predicted communication quality.

[0009] A non-transient computer-readable storage medium is provided. The non-transient computer-readable storage medium may store one or more programs. The one or more programs may be executed by an electronic device having a wireless communication circuit and a camera. The one or more programs may include instructions that cause the electronic device to obtain first information corresponding to a wireless access node device located within a wireless communication range with the electronic device via the wireless communication circuit when executed by the electronic device. The instructions may include instructions that cause the electronic device to obtain second information corresponding to a candidate spot near the electronic device based at least partially on an image corresponding to the surroundings of the electronic device obtained through the camera when executed individually or collectively by the at least one processor. The instructions may include instructions that cause the electronic device to estimate the predicted communication quality for the wireless access node device at the candidate spot based at least partially on the first information and the second information when executed individually or collectively by the at least one processor. The above instructions may include instructions that cause the electronic device to provide third information corresponding to a recommended spot for performing wireless communication through the wireless access node device, based at least in part on the predicted communication quality, when executed individually or collectively by the at least one processor.

[0010] Figure 1 is a schematic view of an exemplary electronic device.

[0011] FIGS. 2A and 2B illustrate examples according to one embodiment of a head-wearable electronic device.

[0012] FIG. 2c illustrates an example according to one embodiment of a head-wearable electronic device.

[0013] FIGS. 2D and FIGS. 2E illustrate examples according to one embodiment of a head-wearable electronic device.

[0014] Figure 3 illustrates an example of the usage environment of an electronic device.

[0015] Figure 4 is a block diagram showing a configuration for identifying candidate spots for Wi-Fi use.

[0016] FIG. 5 illustrates a data exchange environment that is generated to identify candidate spots for Wi-Fi usage in accordance with a user's query within an electronic device.

[0017] FIG. 6a is a flowchart illustrating a method for visually displaying recommended spots for Wi-Fi use based on events for Wi-Fi use within an electronic device.

[0018] FIG. 6b is a flowchart illustrating a method of providing information about recommended spots for Wi-Fi use through a speaker based on an event for Wi-Fi use within an electronic device.

[0019] Figure 7 is an example of an environment in which the location of an AP device is determined based on the locations of electronic devices identified through sensors of electronic devices and wireless communication signals received from the AP device.

[0020] Figure 8 is an example of an environment in which the location of a candidate spot for Wi-Fi use is determined based on image data acquired through a camera of an electronic device.

[0021] Figure 9 is an example of an environment for determining the estimated throughput when accessing an AP device from a candidate spot based on the attributes of obstacles within the communication path for accessing an AP device from a candidate spot for Wi-Fi use.

[0022] Figure 10 is a graph illustrating the throughput determined by the properties of obstacles within the communication path for accessing an AP device at a candidate spot location for Wi-Fi use.

[0023] FIG. 11 is an example of an environment in which the estimated throughput is determined when accessing an AP device from a candidate spot based on interference from external electronic devices around a candidate spot for Wi-Fi use.

[0024] FIGS. 12a and 12b illustrate examples of environments that visually display recommended spots for Wi-Fi use based on events for Wi-Fi use within an electronic device.

[0025] FIG. 12c illustrates an example of an environment in which information about recommended spots for Wi-Fi use is provided through a speaker based on an event for Wi-Fi use within an electronic device.

[0026] FIG. 13 is an example of an environment that provides information about recommended spots in a space where multiple AP devices exist based on an event for the use of Wi-Fi within an electronic device.

[0027] FIG. 14 is a flowchart illustrating a method for providing information corresponding to a recommended spot based on the estimation of the predicted communication quality for a wireless access node device at a candidate spot.

[0028] FIGS. 15a and FIGS. 15b are drawings illustrating an example of identifying candidate spots for the installation of an AP device.

[0029] FIGS. 16a and FIGS. 16b are drawings to illustrate an example of providing information on the estimated throughput when accessing a base station at a user's destination.

[0030] FIG. 17 is a block diagram of an electronic device in a network environment according to various embodiments.

[0031] FIG. 18 is a schematic diagram of an exemplary AI system according to one embodiment.

[0032] Figure 1 is a schematic view of an exemplary electronic device.

[0033] According to one embodiment, referring to FIG. 1, the electronic device (101) may include at least one processor (110), memory (120), camera (130), at least one display (140), microphone (150), speaker (160), at least one sensor (170), and / or communication circuit (180). For example, the electronic device (101) may have various embodiments. For example, the electronic device (101) may be described as a portable device (e.g., a smartphone and / or a tablet). For example, the electronic device (101) may be described as a glasses-type wearable device, a head-wearable electronic device, and / or a head-mounted wearable device. However, the present disclosure is not limited thereto. For example, the present disclosure may be applicable to any electronic device having a communication circuit for the use of a camera and / or Wi-Fi (wireless fidelity). For example, the electronic device (101) may include at least a part of the electronic device (1701) of FIG. 17 or correspond to at least a part of the electronic device (1701) of FIG. 17.

[0034] According to one embodiment, at least one processor (110) may include a processing circuit. At least one processor (110) may include a single processor or multiple processors. At least one processor (110) may control the memory (120) and / or one or more components (e.g., camera (130), at least one display (140), microphone (150), speaker (160), at least one sensor (170), and / or communication circuit (180)) of the electronic device (101). For example, at least one processor (110) may include at least a part of the processor (1720) of FIG. 17 or correspond to at least a part of the processor (1720) of FIG. 17.

[0035] According to one embodiment, the memory (120) may store one or more programs configured to be executed individually and / or collectively by at least one processor (110). The one or more programs may include instructions. The instructions may cause the electronic device (101) to perform operations described with reference to FIGS. 2a through 16b. The memory (120) may include one or more storage media. At least some of the one or more programs may be available to manage, control, and / or execute a trained model described below. For example, the memory (120) may include at least some of the memory (1730) of FIG. 17 or correspond to at least some of the memory (1730) of FIG. 17.

[0036] According to one embodiment, the camera (130) may capture (or take) an image (e.g., a still image) and / or video. For example, the camera (130) may include one or more lenses, image sensors, and / or flashes. For example, the camera (130) may include at least a part of the camera (240) of FIG. 2b or correspond to at least a part of the camera (240) of FIG. 2b. For example, the camera (130) may include at least a part of the camera (294) of FIG. 2c and FIG. 2d or correspond to at least a part of the camera (294) of FIG. 2c and FIG. 2d. For example, the camera (130) may include at least a part of the camera module (1780) of FIG. 17 or correspond to at least a part of the camera module (1780) of FIG. 17.

[0037] According to one embodiment, at least one display (140) can visually provide information to an external (e.g., user) outside of the electronic device (101). For example, at least one display (140) may include a first display and a second display spaced apart from each other. For example, the first display may be placed within the housing of the electronic device (101) at a position corresponding to the user's left eye, and the second display may be placed within the housing of the electronic device (101) at a position corresponding to the user's right eye. For example, at least one display (140) may include a display panel and / or a touch sensor. For example, the display panel may be used to display visual information (e.g., images, screens, objects, UI (user interface), GUI (graphic user interface), and / or visual objects). For example, the display panel may have a display area capable of receiving touch input. For example, the touch sensor may be used to obtain data about an external object located on the display panel. For example, the touch sensor may be located within or on the display panel to provide an area of ​​the display panel capable of receiving the touch input. For example, the touch sensor may be configured to acquire data for contact points on at least a portion of the area. For example, at least one display (140) may include at least a portion of at least one display (230) of FIG. 2A or correspond to at least a portion of at least one display (230) of FIG. 2A. For example, at least one display (140) may include at least a portion of at least one display (293) of FIG. 2C and FIG. 2D or correspond to at least a portion of at least one display (293) of FIG. 2C and FIG. 2D.For example, at least one display (140) may include at least a part of the display module (1760) of FIG. 17 or correspond to at least a part of the display module (1760) of FIG. 17.

[0038] According to one embodiment, the microphone (150) can detect (or identify) sounds in the surrounding environment of the electronic device (101). For example, the microphone (150) can detect the voice of a user of the electronic device (101). The microphone (150) can convert the detected sound into a signal and transmit the converted signal to at least one processor (110). For example, the microphone (150) may include at least a part of the input module (1750) of FIG. 17 or correspond to at least a part of the input module (1750) of FIG. 17.

[0039] According to one embodiment, the speaker (160) can output sound to the outside of the electronic device (101) (e.g., a user) based on audio data identified by at least one processor (110). For example, the speaker (160) may include at least a part of the sound output module (1755) of FIG. 17 or correspond to at least a part of the sound output module (1755) of FIG. 17.

[0040] According to one embodiment, at least one sensor (170) may include one or more sensors for detecting (or identifying) the position of an electronic device (101). For example, the one or more sensors may include an acceleration sensor that detects the linear acceleration of the electronic device (101) and / or a gyroscope sensor that detects the rotational angular velocity of the electronic device (101). For example, the one or more sensors may identify the distance traveled and the direction of travel of the electronic device (101) based on the linear acceleration and / or the rotational angular velocity. For example, the one or more sensors may be referred to as an inertia measurement unit (IMU) sensor. For example, at least one sensor (170) may include at least a part of the sensor module (1776) of FIG. 17 or correspond to at least a part of the sensor module (1776) of FIG. 17.

[0041] According to one embodiment, the communication circuit (180) (or wireless communication circuit) may support the establishment of a communication channel for a wireless network (e.g., Wi-Fi (wireless fidelity)) and the performance of communication through the established communication channel. For example, the communication circuit (180) may include at least a part of the communication module (1790) of FIG. 17 or correspond to at least a part of the communication module (1790) of FIG. 17.

[0042] FIGS. 2A and 2B illustrate examples according to one embodiment of a head-wearable electronic device.

[0043] According to one embodiment, with reference to FIG. 2a, an example of a perspective view of an electronic device (101) is shown. With reference to FIG. 2b, an example of one or more hardware components disposed within the electronic device (101) is shown. The electronic device (101) shown in FIG. 2a and FIG. 2b may be referred to as a head-wearable electronic device that can be worn on a user's head. For example, the electronic device (101) shown in FIG. 2a and FIG. 2b may be referred to as augmented reality (AR) glasses that provide an augmented reality image combined with a virtual reality image displayed through a display on a real-world screen transmitted through a display.

[0044] According to one embodiment, the electronic device (101) may be worn on a part of a user's body. The electronic device (101) may provide augmented reality (AR), virtual reality (VR), or mixed reality (MR) that combines augmented reality and virtual reality to the user wearing the electronic device (101). For example, the electronic device (101) may display a virtual reality image provided by at least one optical device (282, 284) of FIG. 2b on at least one display (230) in response to a specified gesture of the user obtained through the motion recognition camera (240-2) of FIG. 2b.

[0045] According to one embodiment, at least one display (230) can provide visual information to a user. For example, at least one display (230) may include a transparent or translucent lens. At least one display (230) may include a first display (230-1) and / or a second display (230-2) spaced apart from the first display (230-1). For example, the first display (230-1) and the second display (230-2) may be positioned at locations corresponding to the user's left and right eyes, respectively.

[0046] According to one embodiment, referring to FIG. 2b, at least one display (230) may provide visual information transmitted from external light to a user through a lens included in at least one display (230) and other visual information distinct from said visual information. The lens may be formed based on at least one of a Fresnel lens, a pancake lens, or a multi-channel lens. For example, at least one display (230) may include a first surface (231) and a second surface (232) opposite to the first surface (231). A display area may be formed on the second surface (232) of at least one display (230). When a user wears the electronic device (101), external light may be transmitted to the user by being incident on the first surface (231) and transmitted through the second surface (232). As another example, at least one display (230) can display an augmented reality image combined with a virtual reality image provided by at least one optical device (282, 284) on a real image transmitted through external light in a display area formed on a second surface (232).

[0047] According to one embodiment, at least one display (230) may include at least one waveguide (233, 234) that diffracts light emitted from at least one optical device (282, 284) and transmits it to a user. At least one waveguide (233, 234) may be formed based on at least one of glass, plastic, or polymer. A nano pattern may be formed on the exterior or at least a portion of the interior of at least one waveguide (233, 234). The nano pattern may be formed based on a polygonal and / or curved grating structure. Light incident on one end of at least one waveguide (233, 234) may be propagated to the other end of at least one waveguide (233, 234) by the nano pattern. At least one waveguide (233, 234) may include at least one diffractive element (e.g., DOE (diffractive optical element), HOE (holographic optical element)) and at least one reflective element (e.g., a reflective mirror). For example, at least one waveguide (233, 234) may be placed within an electronic device (101) to guide a screen displayed by at least one display (230) to the user's eye. For example, the screen may be transmitted to the user's eye based on total internal reflection (TIR) ​​occurring within at least one waveguide (233, 234).

[0048] According to one embodiment, the frame (200) may be formed as a physical structure that allows the electronic device (101) to be worn on the user's body. According to one embodiment, the frame (200) may be configured so that when the user wears the electronic device (101), the first display (230-1) and the second display (230-2) can be positioned corresponding to the user's left and right eyes. The frame (200) may support at least one display (230). For example, the frame (200) may support the first display (230-1) and the second display (230-2) so that they are positioned corresponding to the user's left and right eyes.

[0049] According to one embodiment, referring to FIG. 2a, the frame (200) may include an area (220) in which at least a portion of the frame (200) comes into contact with a portion of the user's body when the user wears the electronic device (101). For example, the area (220) of the frame (200) in contact with a portion of the user's body may include a portion of the user's nose, a portion of the user's ear, and / or a portion of the side of the user's face that the electronic device (101) comes into contact with. According to one embodiment, the frame (200) may include a nose pad (210) that comes into contact with a portion of the user's body. When the electronic device (101) is worn by the user, the nose pad (210) may come into contact with a portion of the user's nose. The frame (200) may include a first temple (204) and / or a second temple (205) that come into contact with another portion of the user's body that is distinct from the portion of the user's body.

[0050] According to one embodiment, the frame (200) may include a first rim (201) covering at least a portion of a first display (230-1), a second rim (202) covering at least a portion of a second display (230-2), a bridge (203) disposed between the first rim (201) and the second rim (202), a first pad (211) disposed along a portion of the edge of the first rim (201) from one end of the bridge (203), a second pad (212) disposed along a portion of the edge of the second rim (202) from the other end of the bridge (203), a first temple (204) extending from the first rim (201) and fixed to a portion of the wearer's ear, and / or a second temple (205) extending from the second rim (202) and fixed to a portion of the ear opposite to the ear. The first pad (211) and / or the second pad (212) may come into contact with a part of the user's nose, and the first temple (204) and / or the second temple (205) may come into contact with a part of the user's face and / or a part of the ear. The temples (204, 205) may be rotatably connected to the rim through the hinge units (206, 207) of FIG. 2B. The first temple (204) may be rotatably connected to the first rim (201) through the first hinge unit (206) positioned between the first rim (201) and the first temple (204). The second temple (205) may be rotatably connected to the second rim (202) through the second hinge unit (207) positioned between the second rim (202) and the second temple (205). According to one embodiment, the electronic device (101) can identify an external object (e.g., a user's fingertip) touching the frame (200) and / or a gesture performed by said external object by using a touch sensor, a grip sensor, and / or a proximity sensor formed on at least a portion of the surface of the frame (200).

[0051] According to one embodiment, the electronic device (101) may include hardware that performs various functions. For example, the hardware may include a battery module (270), an antenna module (275), at least one optical device (282, 284), a light-emitting module (not shown), and / or a printed circuit board (290). The various hardware may be placed within a frame (200).

[0052] According to one embodiment, a microphone (150) of an electronic device (101) may be placed on at least a portion of a frame (200) to acquire a sound signal. The microphone (150) may include a first microphone placed on a nose pad (210), a second microphone placed on a first rim (201), and / or a third microphone placed on a second rim (202). If there are two or more microphones (150) included in the electronic device (101), the electronic device (101) may identify the direction of the sound signal by using a plurality of microphones placed on different portions of the frame (200).

[0053] According to one embodiment, at least one optical device (282, 284) may project a virtual object onto at least one display (230) to provide various image information to a user. For example, at least one optical device (282, 284) may be a projector. At least one optical device (282, 284) may be disposed adjacent to at least one display (230) or included within at least one display (230) as part of at least one display (230). According to one embodiment, the electronic device (101) may include a first optical device (282) corresponding to a first display (230-1) and / or a second optical device (284) corresponding to a second display (230-2). For example, at least one optical device (282, 284) may include a first optical device (282) positioned at the edge of the first display (230-1) and / or a second optical device (284) positioned at the edge of the second display (230-2). The first optical device (282) may transmit light to a first waveguide (233) positioned on the first display (230-1), and the second optical device (284) may transmit light to a second waveguide (234) positioned on the second display (230-2).

[0054] According to one embodiment, the camera (240) may include a shooting camera, an eye tracking camera (ET CAM) (240-1), a motion recognition camera (240-2), and / or a shooting camera (240-3). The eye tracking camera (240-1), the motion recognition camera (240-2), and / or the shooting camera (240-3) may be positioned at different locations on the frame (200) and may perform different functions. The eye tracking camera (240-1) may output data indicating the gaze of a user wearing the electronic device (101). For example, the electronic device (101) may detect the gaze from an image containing the user's pupils obtained through the eye tracking camera (240-1). An example in which the eye tracking camera (240-1) is positioned toward the user's right eye is illustrated in FIG. 2b, but the present disclosure is not limited thereto, and the eye tracking camera (240-1) may be positioned solely toward the user's left eye or toward both eyes.

[0055] According to one embodiment, the eye tracking camera (240-1) can achieve more realistic augmented reality by tracking the gaze of a user wearing the electronic device (101), thereby matching the user's gaze with visual information provided to at least one display (230). For example, when the user looks straight ahead, the electronic device (101) can naturally display environmental information related to the user's front at the location where the user is situated on at least one display (230). The eye tracking camera (240-1) may be configured to capture an image of the user's pupil to determine the user's gaze. For example, the eye tracking camera (240-1) may receive a gaze detection light reflected from the user's pupil and track the user's gaze based on the position and / or movement of the received gaze detection light. In one embodiment, the eye tracking camera (240-1) may be positioned at locations corresponding to the user's left and right eyes. For example, the eye-tracking camera (240-1) may be positioned within the first rim (201) and / or the second rim (202) to face the direction in which the user wearing the electronic device (101) is located.

[0056] According to one embodiment, a motion recognition camera (240-2) can provide a specific event to a screen provided on at least one display (230) by recognizing the movement of the user's entire body or part thereof, such as the user's torso, hands, or face. The motion recognition camera (240-2) can recognize the user's gesture, acquire a signal corresponding to the gesture, and provide a display corresponding to the signal to at least one display (230). A processor can identify the signal corresponding to the gesture and, based on the identification, perform a designated function. In one embodiment, the motion recognition camera (240-2) may be placed on a first rim (201) and / or a second rim (202).

[0057] According to one embodiment, the camera (240-3) can capture a real image or background to be matched with a virtual image in order to implement augmented reality or mixed reality content. The camera (240-3) can capture an image of a specific object located at the position viewed by the user and provide the image to at least one display (230). The at least one display (230) can display a single image in which information regarding a real image or background including the image of the specific object obtained using the camera (240-3) and a virtual image provided through at least one optical device (282, 284) are superimposed. In one embodiment, the camera (240-3) can be placed on a bridge (203) positioned between the first rim (201) and the second rim (202). The electronic device (101) can analyze an object included in a real-world image collected through a camera (240-3), combine a virtual object corresponding to an object among the analyzed objects that is the target of augmented reality provision, and display it on at least one display (230). The virtual object may include at least one of text and / or images regarding various information related to the object included in the real-world image. The electronic device (101) can analyze the object based on a multi-camera such as a stereo camera. For the object analysis, the electronic device (101) can perform time-of-flight (ToF) and / or simultaneous localization and mapping (SLAM) supported by the multi-camera. A user wearing the electronic device (101) can view the image displayed on at least one display (230).

[0058] According to one embodiment, the camera (240) included in the electronic device (101) is not limited to the eye-tracking camera (240-1), motion recognition camera (240-2), and / or shooting camera (240-3) described above. For example, the electronic device (101) can identify an external object included in the FoV by using a camera (240) positioned toward the user's FoV. The identification of the external object by the electronic device (101) can be performed based on a sensor for identifying the distance between the electronic device (101) and the external object, such as a depth sensor and / or a time of flight (ToF) sensor. The camera (240) positioned toward the FoV may support an autofocus function and / or an optical image stabilization (OIS) function. For example, the electronic device (101) may include a camera (240) (e.g., a face tracking camera) positioned toward the face to obtain an image including the face of a user wearing the electronic device (101).

[0059] Although not illustrated, according to one embodiment, the electronic device (101) may further include a light source (e.g., LED) that emits light toward a subject (e.g., user's eye, face, and / or an object outside the FoV) being photographed using a camera (240). The light source may include an LED of infrared wavelength. The light source may be placed in at least one of the frame (200) and hinge units (206, 207).

[0060] According to one embodiment, the battery module (270) can supply power to the electronic components of the electronic device (101). In one embodiment, the battery module (270) may be placed within the first temple (204) and / or the second temple (205). For example, the battery module (270) may be a plurality of battery modules (270). The plurality of battery modules (270) may each be placed in the first temple (204) and the second temple (205). In one embodiment, the battery module (270) may be placed at the end of the first temple (204) and / or the second temple (205).

[0061] According to one embodiment, the antenna module (275) may transmit a signal or power to the outside of the electronic device (101) or receive a signal or power from the outside. The antenna module (275) may be electrically and / or operationally connected to a communication circuit. In one embodiment, the antenna module (275) may be placed within the first temple (204) and / or the second temple (205). For example, the antenna module (275) may be placed close to one side of the first temple (204) and / or the second temple (205).

[0062] According to one embodiment, the speaker (160) can output an acoustic signal to the outside of the electronic device (101). The acoustic output module may be referred to as the speaker. In one embodiment, the speaker (160) may be placed within a first temple (204) and / or a second temple (205) to be positioned adjacent to the ear of a user wearing the electronic device (101). For example, the speaker (160) may include a first speaker positioned adjacent to the user's left ear by being placed within the first temple (204) and / or a second speaker positioned adjacent to the user's right ear by being placed within the second temple (205).

[0063] According to one embodiment, a light-emitting module (not shown) may include at least one light-emitting element. The light-emitting module may emit light of a color corresponding to a specific state or emit light with an action corresponding to a specific state in order to visually provide information regarding a specific state of the electronic device (101) to the user. For example, if the electronic device (101) requires charging, it may emit red light at a constant frequency. In one embodiment, the light-emitting module may be placed on a first rim (201) and / or a second rim (202).

[0064] According to one embodiment, referring to FIG. 2b, the electronic device (101) may include a printed circuit board (PCB) (290). The PCB (290) may be included in at least one of a first temple (204) or a second temple (205). The PCB (290) may include an interposer disposed between at least two sub-PCBs. One or more hardware components included in the electronic device (101) may be disposed on the PCB (290). The electronic device (101) may include a flexible PCB (FPCB) for interconnecting the hardware components.

[0065] According to one embodiment, the electronic device (101) may include at least one of a gyroscope sensor, a gravity sensor, and / or an acceleration sensor for detecting the posture of the electronic device (101) and / or the posture of a body part (e.g., head) of a user wearing the electronic device (101). Each of the gravity sensor and the acceleration sensor may measure gravitational acceleration and / or acceleration based on designated three-dimensional axes (e.g., x-axis, y-axis, and / or z-axis) that are perpendicular to each other. The gyroscope sensor may measure the angular velocity of each of the designated three-dimensional axes (e.g., x-axis, y-axis, and / or z-axis). At least one of the gravity sensor, the acceleration sensor, and the gyroscope sensor may be referred to as an inertial measurement unit (IMU). According to one embodiment, the electronic device (101) may identify motions and / or gestures of a user performed to execute or interrupt specific functions of the electronic device (101) based on the IMU. FIGS. 2a and 2b are illustrated in the form of AR glasses, but are not limited thereto. For example, the electronic device (101) may include an HMD device and / or a VST (video see-through) device. For example, the VST device may provide a UI for mixed reality (MR) based on a device worn on a user's head, such as an HMD device.

[0066] FIG. 2c illustrates an example according to one embodiment of a head-wearable electronic device.

[0067] According to one embodiment, with reference to FIG. 2c, an example of one or more hardware components disposed within an electronic device (101) is illustrated. The electronic device (101) illustrated in FIG. 2c may be referred to as a head-wearable electronic device that can be worn on a user's head. For example, the electronic device (101) illustrated in FIG. 2c may be referred to as artificial intelligence (AI) glasses having a processor and / or memory for managing, executing, and / or controlling a model trained using learning data. For example, the electronic device (101) illustrated in FIG. 2c may be described as a device in which at least one display (230), at least one waveguide (233, 234) associated with at least one display (230), and at least one optical device (282, 284) are omitted from the configurations of the electronic device described with reference to FIG. 2a and FIG. 2b.

[0068] FIGS. 2D and FIGS. 2E illustrate examples according to one embodiment of a head-wearable electronic device.

[0069] According to one embodiment, with reference to FIG. 2d, an example of a first surface (291) of a housing included in an electronic device (101) is shown. With reference to FIG. 2e, an example of a second surface (292) opposite to the first surface (291) of the housing included in the electronic device (101) is shown.

[0070] According to one embodiment, with reference to FIG. 2d, the first surface (291) of the electronic device (101) may have a shape that is attachable to a part of a user's body (e.g., the user's face). Although not illustrated, the electronic device (101) may further include a strap and / or one or more temples for securing to a part of a user's body.

[0071] According to one embodiment, the electronic device (101) may include at least one display (293), a camera (294), and a depth sensor (295).

[0072] According to one embodiment, at least one display (293) may include a first display (293-1) and a second display (293-2) disposed on a first surface (291). The first display (293-1) may output an image to the left eye among the user's two eyes, and the second display (293-2) may output an image to the right eye among the user's two eyes. The electronic device (101) may further include a rubber or silicone packing formed on the first surface (291) to prevent interference by light different from the light emitted from the first display (293-1) and the second display (293-2) (e.g., ambient light).

[0073] According to one embodiment, the camera (294) may include a camera (294-1), a camera (294-2), a camera (294-3), a camera (294-4), a camera (294-5), a camera (294-6), a camera (294-7), a camera (294-8), a camera (294-9), and a camera (294-10).

[0074] According to one embodiment, with reference to FIG. 2d, the electronic device (101) may include cameras (294-1, 294-2) for photographing and / or tracking both eyes of a user adjacent to each of the first display (293-1) and the second display (293-2). According to one embodiment, the electronic device (101) may include cameras (294-3, 294-4) for photographing and / or recognizing the face of a user.

[0075] According to one embodiment, referring to FIG. 2e, cameras (294-5, 294-6, 294-7, 294-8, 294-9, 294-10) and a depth sensor (295) may be disposed on a second surface (292) opposite to the first surface (291) of FIG. 2d to acquire information related to the external environment of the electronic device (101). For example, cameras (294-5), (294-6), (294-7), and (294-8) may be disposed on the second surface (292) to recognize external objects different from the electronic device (101). For example, the electronic device (101) may acquire images and / or videos to be transmitted to each of the user's eyes using cameras (294-9) and (294-10). A camera (294-9) may be placed on a second surface (292) of the electronic device (101) to acquire an image to be displayed through a second display (293-2) corresponding to the right eye among the user's two eyes. A camera (294-10) may be placed on a second surface (292) of the electronic device (101) to acquire an image to be displayed through a first display (293-1) corresponding to the left eye among the user's two eyes.

[0076] According to one embodiment, a depth sensor (295) may be placed on a second surface (292) to identify the distance between the electronic device (101) and an external object. The electronic device (101) may use the depth sensor (295) to obtain spatial information (e.g., a depth map) for at least a portion of the field of view (FOV) of a user wearing the electronic device (101).

[0077] Although not illustrated, according to one embodiment, a microphone (150) for acquiring sound output from an external object may be placed on a second surface (292) of the electronic device (101). The number of microphones may vary depending on the embodiment.

[0078] According to one embodiment, the electronic device (101) may have an embodiment distinct from the embodiments shown in FIG. 2a, 2b, 2c, 2d, and 2e. For example, the electronic device (101) may be implemented as a portable device (e.g., a smartphone and / or a tablet).

[0079] Figure 3 illustrates an example of the usage environment of an electronic device.

[0080] According to one embodiment, with reference to FIG. 3, a usage environment (300) is shown in which a user (301) wearing and / or carrying an electronic device (101) within a place (310) associated with an event for the use of Wi-Fi (wireless fidelity) uses the electronic device (101).

[0081] According to one embodiment, the place (310) may be described as a place (e.g., a coffee shop) where an access point (AP) device (321) (or wireless access node device) is located, which provides a wireless network for wireless fidelity (Wi-Fi) to surrounding electronic devices. For example, the wireless access node device may be described as at least one of an access point of a wireless fidelity (Wi-Fi) network and a base station of a cellular network.

[0082] According to one embodiment, the place (310) may have a spot (311), a spot (312), and / or a spot (313) for a user (301) using Wi-Fi through an electronic device (101). By example, without limitation, each of the spot (311), spot (312), and spot (313) may be described as a spot where a table is located within the place (310). For example, the place (310) may have an area (314) where an AP device (321) is located. The area (314) may be described as a checkout counter located within the place (310). For example, the area (314) may have an object (322) containing information about the Wi-Fi ID (identifier) ​​and / or password provided through the AP device (321).

[0083] According to one embodiment, an electronic device (101) can identify an event for the use of Wi-Fi based on user input (302) for using Wi-Fi through the electronic device (101) within a place (310). For example, user input (302) may be described as voice input by the user (301) and / or touch input (e.g., text input) on at least one display (140). A method of operation in which the electronic device (101) identifies candidate spots for the use of Wi-Fi within a place associated with an event for the use of Wi-Fi is described with reference to FIGS. 4 through 14.

[0084] Figure 4 is a block diagram showing a configuration for identifying candidate spots for Wi-Fi use.

[0085] According to one embodiment, with reference to FIG. 4, an environment (400) for identifying candidate spots for Wi-Fi use within a location associated with an event for Wi-Fi use is illustrated. The environment (400) may include a first trained model (401), a second trained model (402), an AP location determination unit (403), a candidate spot location determination unit (404), a third trained model (405), a fourth trained model (406), and / or a fifth trained model (407). Each of the AP location determination unit (403) and the candidate spot location determination unit (404) may be described as a program executed by at least one processor (110) and stored in memory (120). Each of the first trained model (401), the second trained model (402), the third trained model (405), the fourth trained model (406), and the fifth trained model (407) may be described as an AI model (e.g., an on-device AI model) executed by at least one processor (110) of the electronic device (101) or an AI model executed by a processor of an external electronic device. For example, each of the first trained model (401), the second trained model (402), the third trained model (405), the fourth trained model (406), and the fifth trained model (407) may include one or more calculations for identifying candidate spots for Wi-Fi use and / or a calculation model for performing said one or more calculations. In the following description, the present disclosure is described based on an example in which a first trained model (401), a second trained model (402), a third trained model (405), a fourth trained model (406), and / or a fifth trained model (407) are executed by at least one processor (110). The number of training models is not limited to that shown in FIG. 4.For example, two or more of the training models shown in FIG. 4 may be integrated, or at least one training model not shown in FIG. 4 may be added to the configuration of FIG. 4.

[0086] According to one embodiment, an electronic device (101) can identify an event for the use of Wi-Fi based on user input for the use of Wi-Fi through a first trained model (401). For example, the user input may be described as data based on the user's voice input and / or touch input (e.g., text input) on at least one display (140). For example, the first trained model (401) may be described as an AI model trained to identify user data stored in the memory (120) of the electronic device (101) according to the user input. The electronic device (101) can obtain past history information (or usage history information) regarding the execution of a software application for a location associated with the event, based on the event for the use of Wi-Fi through the first trained model (401), by using the software application. For example, the software application may be described as a software application executable for making payments and / or ordering goods within a place associated with the event (e.g., a coffee shop). For example, the historical information may include information about the time when the software application was executed. The electronic device (101) may obtain user pattern information regarding the use of Wi-Fi based on the event for the use of Wi-Fi through the first trained model (401). For example, the user pattern information may include information about the time when Wi-Fi was used and / or information about the type of software application executed via Wi-Fi.

[0087] According to one embodiment, the electronic device (101) can apply user input, image data, past history information, and / or user pattern information to a second trained model (402) and identify context information obtained from the second trained model (402). For example, the image data may be obtained through a camera (130). For example, the image data may be described as data for an image (e.g., a preview image) to be displayed through at least one display (140). For example, the second trained model (402) may be described as an AI model trained to identify the context of the user input based on user data stored in the memory (120) of the electronic device (101). For example, the context information may include information associated with the context of the user input. For example, the electronic device (101) can identify, through a second trained model (402), an operation of the electronic device (101) that was executed via Wi-Fi during the time interval in which application software for the location associated with the event was executed. As an example without limitation, the electronic device (101) can obtain context information indicating that the estimated throughput (or predicted communication quality) when accessing an access point (AP) device at a candidate spot within the location associated with the event is required of the user, based on the identification of the operation executed via Wi-Fi (e.g., video playback). Throughput can be described in various ways.For example, throughput can represent the effective speed of data transmission depending on the characteristics of the receiver, the characteristics of the transmitter, and / or the environment associated with the receiver and / or transmitter.

[0088] According to one embodiment, an electronic device (101) can obtain target AP information through a second trained model (402). For example, the target AP information can identify the AP device for the event among the AP devices around the electronic device (101) using identifier information (e.g., service set identifier, SSID) for each of the identifiers of the AP devices. For example, the identifier information may be included in wireless communication signals (e.g., beacon signals) received from the AP devices. For example, the electronic device (101) can identify identifier information corresponding to the AP device for the event among the AP devices based on image data obtained through a camera (130). For example, the electronic device (101) can identify an object (e.g., 322 in FIG. 3) containing information about a Wi-Fi ID within the location associated with the event using the image data. For example, the electronic device (101) can identify information about the Wi-Fi ID from the object and identify the identifier information corresponding to the identified information as identifier information corresponding to the AP device.

[0089] According to one embodiment, an electronic device (101) can identify a first location data (location data 1) indicating the location of an AP device for the event based on target AP information, sensing data, and / or wireless communication signals. For example, the first location data may indicate the location of an AP device defined for the electronic device (101). For example, the sensing data may indicate the location of the electronic device (101) detected (or identified) through at least one sensor (170). For example, the wireless communication signals may be received from the AP device periodically or non-periodically. For example, the electronic device (101) may determine the location of the AP device based on the locations of the electronic device (101) based on the sensing data and / or the received signal strength indicator (RSSI) of the wireless communication signal. An operation method for determining the location of an AP device for Wi-Fi use is described in detail below with reference to FIG. 7.

[0090] According to one embodiment, the electronic device (101) can identify second location data (location data 2) representing the locations of candidate spots for Wi-Fi use within the location associated with the event, based on first location data (location data 1) and / or image data. For example, the second location data may represent the locations of candidate spots defined for the electronic device (101) and / or the AP device. For example, each of the candidate spots may be described as a spot located within the location associated with the event and for accessing the AP device. For example, the electronic device (101) may obtain a depth map from the image data representing the depth of each of the objects included in the image data. For example, the electronic device (101) may identify the locations of each of the candidate spots defined for the electronic device (101) based on the obtained depth map. For example, the electronic device (101) can identify angles between the location of the AP device and the location of each of the candidate spots with respect to the location of the electronic device (101) based on the first location data and / or the image data. For example, the electronic device (101) can identify the second location data based on the identified angles and the location of each of the candidate spots defined with respect to the electronic device (101).

[0091] According to one embodiment, the electronic device (101) can acquire scene understanding data based on image data through a third trained model (405). For example, the third trained model (405) may be described as an AI model trained for vision recognition (e.g., object recognition, spatial analysis, and / or contextual understanding) to estimate Wi-Fi throughput based on image data acquired through a camera (130). For example, the scene understanding data may include path information regarding whether a communication path to access the AP device from a candidate spot corresponds to a line of sight (LOS) or a non-line of sight (NLOS). For example, the scene understanding data may include material information, size information, and / or location information regarding obstacles within the communication path to access the AP device from a candidate spot. For example, the scene understanding data may include interference information regarding whether at least one external electronic device exists around the candidate spot.

[0092] According to one embodiment, the electronic device (101) can obtain estimated throughput data representing the estimated throughput when accessing the AP device at a candidate spot based on the second location data 2 and / or scene understanding data through the fourth trained model (406).

[0093] According to one embodiment, the electronic device (101) can determine the distance between the candidate spot and the AP device based on second location data representing the location of the candidate spot defined for the AP device and / or the electronic device (101). For example, the electronic device (101) can determine the estimated throughput when accessing the AP device from the candidate spot according to the distance. For example, the estimated throughput may decrease as the distance increases.

[0094] According to one embodiment, an electronic device (101) can identify path information included in the scene understanding data using the image data, based on second location data representing the location of a candidate spot defined for the AP device and / or the electronic device (101). The path information may include information regarding whether a communication path for accessing the AP device from the candidate spot corresponds to a line of sight (LOS) or a non-line of sight (NLOS). For example, the electronic device (101) can determine the estimated throughput when accessing the AP device from the candidate spot according to the path information. For example, the throughput estimated according to the path information corresponding to the LOS may be greater than the throughput estimated according to the path information corresponding to the NLOS.

[0095] According to one embodiment, the electronic device (101) can identify material information, size information, and / or location information regarding obstacles within a communication path for accessing the AP device from the candidate spot, based on second location data representing the location of a candidate spot defined for the AP device and / or the electronic device (101), using the image data. For example, the material information, the size information, and / or the location information may be included in the scene understanding data. For example, the electronic device (101) may determine the estimated throughput when accessing the AP device from the candidate spot according to the material information, the size information, and / or the location information. For example, the estimated throughput may decrease as the distance decreases.

[0096] According to one embodiment, the electronic device (101) can identify interference information included in the scene understanding data using the image data based on second location data representing the location of a candidate spot defined for the AP device and / or the electronic device (101). For example, the interference information may include information regarding whether at least one external electronic device exists around the candidate spot. For example, the electronic device (101) can determine the estimated throughput when accessing the AP device at the candidate spot based on the interference information.

[0097] According to one embodiment, the electronic device (101) can obtain output data representing at least one recommended spot among candidate spots for Wi-Fi use within the location associated with the event, based on image data, context information, and / or estimated throughput data, through a fifth trained model (407). For example, the fifth trained model (407) may be described as a multimodal AI model trained to process and / or analyze data of various types (e.g., images and / or text) to select candidate spots. For example, the fifth trained model (407) may include a large world model (LWM), a large vision model (LVM), and / or a large multimodal model (LMM).

[0098] According to one embodiment, the output data may be used to guide access to the AP device at the at least one recommended spot. For example, the electronic device (101) may identify the candidate spot as the at least one recommended spot among the candidate spots when the estimated throughput when accessing the AP device at the candidate spot is within a first range. For example, the electronic device (101) may identify the candidate spot as at least one remaining candidate spot that is distinct from the at least one recommended spot among the candidate spots when the estimated throughput when accessing the AP device at the candidate spot is within a second range that is smaller than the first range.

[0099] According to one embodiment, the electronic device (101) may provide information about at least one recommended spot to guide access to the AP device at at least one recommended spot among candidate spots for Wi-Fi use based on output data. For example, the electronic device (101) may display the at least one recommended spot as visually highlighted relative to at least one remaining candidate spot among the candidate spots in an image displayed through at least one display (140) to guide access to the AP device at the at least one recommended spot. For example, the electronic device (101) may output audio about the at least one recommended spot through a speaker (160) or an external speaker (e.g., Bluetooth earphones) functionally connected to the electronic device (101) to guide access to the AP device at the at least one recommended spot.

[0100] According to one embodiment, the electronic device (101) can maximize the convenience of a user of Wi-Fi by providing information on at least one recommended spot to guide access to an AP device among candidate spots for Wi-Fi use within a place associated with an event for Wi-Fi use.

[0101] FIG. 5 illustrates a data exchange environment that is generated to identify candidate spots for Wi-Fi usage in accordance with a user's query within an electronic device.

[0102] According to one embodiment, with reference to FIG. 5, signalings are shown between an artificial intelligence (AI) assistant (502), a multi-AI agent (503), and / or sub-AI agents (504) to generate a response to a user query based on input for a user query provided by a user (501). For example, the AI ​​assistant (502), the multi-AI agent (503), and / or sub-AI agents (504) may be executed by at least one processor (110) of an electronic device (101). For example, the AI ​​assistant (502) may be described as a model trained for natural language processing for a voice assistant. For example, the sub-AI agents (504) may include a first trained model (401), a second trained model (402), a third trained model (405), and / or a fourth trained model (406) as shown in FIG. 4. For example, the multi-AI agent (503) may include a program for managing data exchange between sub-AI agents (504). For example, the multi-AI agent (503) may include the fifth trained model (407) shown in FIG. 4.

[0103] According to one embodiment, a multi-AI agent (503) can manage sub-AI agents (504) trained to perform different functions. For example, the multi-AI agent (503) can generate prompts for each of the sub-AI agents (504).

[0104] According to one embodiment, a multi-AI agent (503) may select at least one AI agent among sub-AI agents (504) based on a user's query (e.g., a query regarding a spot suitable for studying, a query regarding a spot with no people nearby, or a query regarding a spot with low ambient noise). For example, the multi-AI agent (503) may request the transmission of data related to the query (e.g., history information related to the user) to at least one selected agent, and transmit additional prompts to at least one AI agent among the sub-AI agents (504) based on the transmitted data.

[0105] According to one embodiment, the multi-AI agent (503) can identify whether data related to a user's query exists in the sub-AI agents (504). For example, the multi-AI agent (503) can send a request prompt to the sub-AI agent (504) to send the data based on the determination that the data exists. For example, the multi-AI agent (503) can send output data to the AI ​​assistant (502) based on the determination that the data does not exist.

[0106] According to one embodiment, in operation 511, the user (501) may provide input for a user query to the AI ​​assistant (502). For example, the user query may be a user's utterance corresponding to "I'm going to study at a coffee shop. Which seat can you recommend?"

[0107] According to one embodiment, in operation 512, at least one processor (110) can use an AI assistant (502) to identify the input for the user query as a user prompt. For example, the AI ​​assistant (502) can generate a prompt to be applied to sub-AI agents (504) from the user prompt. For example, at least one processor (110) can identify, based on a purpose analysis of the user query, that the purpose of the user query is to study at a coffee shop in order to generate the prompt through the AI ​​assistant (502). For example, at least one processor (110) can generate the prompt based on the purpose analysis. For example, at least one processor (110) can transmit the generated prompt from the AI ​​assistant (502) to a multi-AI agent (503).

[0108] According to one embodiment, in operation 513, at least one processor (110) can use a multi-AI agent (503) to send a request prompt to a first trained model (401) among sub-AI agents (504) to request historical information of a software application associated with the user query and / or user pattern information regarding the use of Wi-Fi associated with the user query, based on the prompt.

[0109] According to one embodiment, in operation 514, at least one processor (110) can transmit the past history information and / or the user pattern information to a multi-AI agent (503) using the first trained model (401) among the sub-AI agents (504) based on the request prompt for the first trained model (401).

[0110] According to one embodiment, in operation 515, at least one processor (110) can use a multi-AI agent (503) to identify, based on the historical information and / or the user pattern information, that the pattern of a user (501) corresponds to a pattern of playing a video via Wi-Fi in a place associated with the use of Wi-Fi (e.g., a coffee shop). Based on the identification of the pattern, at least one processor (110) can use the multi-AI agent (503) to send a request prompt for requesting estimated throughput data (e.g., a prompt for requesting a communication quality inference result related to a user query) to a fourth trained model (406) among the sub-AI agents (504) trained for communication quality inference.

[0111] According to one embodiment, in operation 516, at least one processor (110) can transmit the estimated throughput data to a multi-AI agent (503) based on the request prompt for the fourth trained model (406).

[0112] According to one embodiment, the multi-AI agent (503) may send a prompt requesting inference of communication quality to at least one of a third trained model (405) trained for scene understanding and / or a fourth trained model (406) trained for inference of communication quality. For example, the third trained model (405) and / or the fourth trained model (406) may generate results of inferring communication quality for candidate spots within the user's field of view as part of the estimated throughput data.

[0113] According to one embodiment, in operation 517, at least one processor (110) can obtain output data indicating at least one recommended spot to guide access to the AP device among candidate spots for Wi-Fi use within the location where the AP device is located, based on the estimated throughput data, by using a fifth trained model (407) included in the multi-AI agent (503). At least one processor (110) can transmit the output data from the multi-AI agent (503) to an AI assistant (502). For example, the multi-AI agent (503) can generate the result of inferring communication quality using sub-AI agents (504) as at least part of the output data. For example, the output data may include the number of candidate spots (e.g., tables), the result of inferring communication quality at the candidate spots, and / or the result of inferring the user's expected behavior at the candidate spots (e.g., watching online lectures using a laptop).

[0114] According to one embodiment, in operation 518, at least one processor (110) can provide a response to the user query to the user (501) based on the output data using an AI assistant (502).

[0115] FIG. 6a is a flowchart illustrating a method for visually displaying recommended spots for Wi-Fi use based on events for Wi-Fi use within an electronic device.

[0116] According to one embodiment, referring to FIG. 6a, in operation 601, at least one processor (110) can identify an event for the use of Wi-Fi (wireless fidelity). At least one processor (110) can identify said event for the use of Wi-Fi based on user input for the use of Wi-Fi. For example, said user input may be described as data based on user voice input and / or touch input (e.g., text input) on at least one display (140).

[0117] According to one embodiment, in operation 602, at least one processor (110) can acquire image data for an image to be displayed through at least one display (140) based on the event through a camera (130). For example, at least one processor (110) can activate the camera (130) to acquire the image data based on the identification of the event.

[0118] According to one embodiment, in operation 603, at least one processor (110) can display the image through at least one display (140). For example, at least one processor (110) can display the image as a preview image through at least one display (140).

[0119] According to one embodiment, in operation 604, at least one processor (110) can use the image data to identify candidate spots for Wi-Fi use within a location associated with the event. For example, the location associated with the event may be described as a location where one or more access point (AP) devices and / or candidate spots for accessing the one or more AP devices are located.

[0120] According to one embodiment, in operation 605, at least one processor (110) can receive wireless communication signals from an AP device around the electronic device (101). For example, at least one processor (110) can receive the wireless communication signals from the AP device around the electronic device (101) periodically or non-periodically through the electronic device (101).

[0121] According to one embodiment, in operation 606, at least one processor (110) can identify the location of each of the candidate spots defined for the AP device and / or electronic device (101) using the wireless communication signals and / or the image data.

[0122] According to one embodiment, at least one processor (110) can identify, based on an event for the use of Wi-Fi, an AP device for said event among AP devices around an electronic device (101) using identifier information (e.g., service set identifier, SSID) for each of said AP devices. For example, said identifier information may be included in wireless communication signals (e.g., beacon signals) received from said AP devices. For example, at least one processor (110) can identify identifier information corresponding to said AP device for said event among said AP devices based on image data acquired through a camera (130). For example, at least one processor (110) can use said image data to identify an object (e.g., 322 in FIG. 3) containing information about a Wi-Fi ID within a location associated with said event. For example, at least one processor (110) can identify information about the Wi-Fi ID from the object and identify the identifier information corresponding to the identified information as identifier information corresponding to the AP device.

[0123] According to one embodiment, at least one processor (110) can determine the location of the identified AP device defined for the electronic device (101) based on the location of the electronic device (101) detected (or identified) through at least one sensor (170) and / or the received signal strength indicator (RSSI) of the wireless communication signals received from the identified AP device. For example, the wireless communication signals may be received periodically or non-periodically from the AP device. For example, the wireless communication signals may include a first wireless communication signal, a second wireless communication signal, and / or a third wireless communication signal received sequentially from the identified AP device. For example, at least one processor (110) can determine a first location of the electronic device (101) identified through at least one sensor (170) and / or a first distance corresponding to the RSSI of the first wireless communication signal based on the reception of the first wireless communication signal. For example, at least one processor (110) may determine a second location of the electronic device (101) identified through at least one sensor (170) and / or a second distance corresponding to the RSSI of the second wireless communication signal based on the reception of the second wireless communication signal. For example, at least one processor (110) may determine a third location of the electronic device (101) identified through at least one sensor (170) and / or a third distance corresponding to the RSSI of the third wireless communication signal based on the reception of the third wireless communication signal. For example, at least one processor (110) may determine the location of the identified AP device defined for the electronic device (101) based on positioning for the identified AP device using the first location, the second location, the third location, the first distance, the second distance, and / or the third distance.For example, the positioning may be performed based on trilateration, which identifies the value of the target coordinate according to three or more reference coordinates and the distances between the reference coordinates and the target coordinate.

[0124] According to one embodiment, at least one processor (110) can identify the location of each of the candidate spots defined for the electronic device (101) based on the image data. For example, at least one processor (110) can obtain a depth map from the image data that indicates the depth of each of the objects included in the image data. For example, the electronic device (101) can identify the location of each of the candidate spots defined for the electronic device (101) based on the obtained depth map.

[0125] According to one embodiment, at least one processor (110) can identify the location of each of the candidate spots defined for the identified AP device and / or the electronic device (101) based on the location of the identified AP device and / or the location of each of the candidate spots defined for the electronic device (101). For example, at least one processor (110) can identify angles between the location of the AP device and the location of each of the candidate spots defined for the location of the electronic device (101) based on the location of the identified AP device and / or the image data. For example, at least one processor (110) can identify the location of each of the candidate spots defined for the identified AP device and / or the electronic device (101) based on the identified angles and / or the location of each of the candidate spots defined for the electronic device (101).

[0126] According to one embodiment, in operation 607, at least one processor (110) can identify at least one recommended spot to guide access to an AP device among the candidate spots based on the location of each of the candidate spots. At least one processor (110) can determine the estimated throughputs when accessing the identified AP device at the candidate spots based on the location of each of the candidate spots. Throughput can be described in various ways. For example, throughput may represent the effective speed of data transmission depending on the characteristics of the receiver, the characteristics of the transmitter, and / or the environment associated with the receiver and / or transmitter. At least one processor (110) can identify the candidate spot as the at least one recommended spot among the candidate spots based on the estimated throughput within a first range. At least one processor (110) can identify the candidate spot as at least one remaining candidate spot among the candidate spots based on the estimated throughput within a second range smaller than the first range.

[0127] According to one embodiment, at least one processor (110) can determine the distance between the candidate spot and the AP device based on the location of the candidate spot defined for the AP device and / or electronic device (101). At least one processor (110) can determine the estimated throughput when accessing the AP device from the candidate spot according to the distance. The estimated throughput may decrease as the distance increases.

[0128] According to one embodiment, at least one processor (110) can identify path information regarding whether a communication path for accessing the AP device from a candidate spot corresponds to a line of sight (LOS) or a non-line of sight (NLOS) based on the location of a candidate spot defined for the AP device and / or electronic device (101), using the image data. For example, at least one processor (110) can identify that the communication path corresponds to an NLOS based on the identification of at least one obstacle existing within the communication path. For example, at least one processor (110) can identify that the communication path corresponds to an LOS based on the identification of no obstacle within the communication path. At least one processor (110) can determine the estimated throughput when accessing the AP device from the candidate spot according to the path information. The throughput estimated according to the path information corresponding to an LOS may be greater than the throughput estimated according to the path information corresponding to an NLOS.

[0129] According to one embodiment, at least one of the wireless communication signals may include bandwidth information regarding the frequency bandwidth (e.g., 2.4 GHz, 5 GHz, 6 GHz) used for the AP device. For example, the estimated throughput may be determined based on the path information and / or the bandwidth information. For example, if the path information corresponds to LOS, the estimated throughput may increase as the frequency bandwidth indicated by the bandwidth information increases. For example, if the path information corresponds to NLOS, the estimated throughput may decrease as the frequency bandwidth indicated by the bandwidth information increases.

[0130] According to one embodiment, at least one processor (110) can identify, using the image data, material information and / or size information for at least one obstacle within a communication path for accessing the AP device at the candidate spot, based on the location of a candidate spot defined for the AP device and / or electronic device (101). For example, the material information may include information about the material of the obstacle present within the communication path (e.g., brick, glass, wood, plastic, and / or concrete). For example, the size information may include information about the width and / or thickness of the obstacle present within the communication path. At least one processor (110) can determine the estimated throughput when accessing the identified AP device at the candidate spot according to the material information and / or size information. For example, at least one processor (110) can identify the distance between each of the identified AP device and the at least one obstacle based on the location of the candidate spot, using the image data. For example, the estimated throughput may decrease as the distance decreases. For example, at least one processor (110) may determine the estimated throughput when accessing the identified AP device at the candidate spot according to the direction of the at least one obstacle defined for the receiver of the identified AP device.

[0131] According to one embodiment, at least one processor (110) can identify, using the image data, interference information regarding whether at least one external electronic device (e.g., microwave oven, laptop, and / or smartphone) exists around the candidate spot based on the location of the candidate spot defined for the identified AP device and / or electronic device (101). At least one processor (110) can determine the estimated throughput when accessing the identified AP device at the candidate spot based on the interference information. For example, at least one processor (110) can use the image data to identify a space (e.g., a bus stop) where interference by an external electronic device existing around the candidate spot is predicted. For example, at least one processor (110) can determine the estimated throughput when accessing the identified AP device at the candidate spot located within the identified space to be lower than that of other spaces.

[0132] According to one embodiment, in operation 608, at least one processor (110) may display the at least one recommended spot in the image displayed through at least one display (140) while being visually highlighted relative to at least one remaining candidate spot among the candidate spots, in order to guide access to the identified AP device at the at least one recommended spot. The method of visually highlighting the at least one recommended spot relative to the at least one remaining candidate spot may be described in various ways according to the embodiment. For example, at least one processor (110) may visually highlight the at least one recommended spot by displaying a visual effect to guide access to the identified AP device at the at least one recommended spot and refraining from displaying the visual effect at the at least one remaining candidate spot. For example, at least one processor (110) may visually highlight the at least one recommended spot by displaying the level of the estimated throughput at each of the candidate spots.

[0133] FIG. 6b is a flowchart illustrating a method of providing information about recommended spots for Wi-Fi use through a speaker based on an event for Wi-Fi use within an electronic device.

[0134] According to one embodiment, referring to FIG. 6b, in operation 611, at least one processor (110) can identify an event for the use of Wi-Fi (wireless fidelity). At least one processor (110) can identify said event for the use of Wi-Fi based on user input for the use of Wi-Fi. For example, said user input may be described as data based on user voice input and / or touch input (e.g., text input) on at least one display (140).

[0135] According to one embodiment, in operation 612, at least one processor (110) can acquire image data for an image to be displayed through at least one display (140) based on the event through a camera (130). For example, at least one processor (110) can activate the camera (130) to acquire the image data based on the identification of the event.

[0136] According to one embodiment, in operation 613, at least one processor (110) can use the image data to identify candidate spots for Wi-Fi use within a location associated with the event. For example, the location associated with the event may be described as a location where one or more AP devices and / or candidate spots for accessing the one or more AP devices are located.

[0137] According to one embodiment, in operation 614, at least one processor (110) can receive wireless communication signals from an AP device around the electronic device (101). For example, at least one processor (110) can receive the wireless communication signals from the AP device around the electronic device (101) periodically or non-periodically through the electronic device (101).

[0138] According to one embodiment, in operation 615, at least one processor (110) can identify the location of each of the candidate spots defined for the AP device and / or electronic device (101) using the wireless communication signals and / or the image data. For example, the method of operation for identifying the location of a candidate spot to guide the use of Wi-Fi may be substantially the same as the method of operation described above in operation 606.

[0139] According to one embodiment, in operation 616, at least one processor (110) can identify at least one recommended spot to guide access to an AP device among the candidate spots based on the location of each of the candidate spots. At least one processor (110) can determine the estimated throughputs when accessing the identified AP device at each of the candidate spots based on the location of each of the candidate spots. At least one processor (110) can identify the at least one recommended spot among the candidate spots based on the estimated throughputs. Throughput can be described in various ways. For example, throughput may represent the effective speed of data transmission depending on the characteristics of the receiver, the characteristics of the transmitter, and / or the environment associated with the receiver and / or transmitter. At least one processor (110) can identify the candidate spot as the at least one recommended spot among the candidate spots based on the estimated throughput within a first range. At least one processor (110) can identify the candidate spot as at least one remaining candidate spot among the candidate spots based on the estimated throughput within a second range smaller than the first range. For example, the method of operation for identifying a candidate spot to guide the use of Wi-Fi may be substantially the same as the method of operation described above in operation 607.

[0140] According to one embodiment, in operation 617, at least one processor (110) may provide (or output) information about the at least one recommended spot through a speaker (160) or an external speaker (e.g., Bluetooth earphones) functionally connected to the electronic device (101) in order to guide access to the identified AP device at the at least one recommended spot.

[0141] Figure 7 is an example of an environment in which the location of an AP device is determined based on the locations of electronic devices identified through sensors of electronic devices and wireless communication signals received from the AP device.

[0142] According to one embodiment, with reference to FIG. 7, an environment (700) is illustrated in which the location of an AP device (711) is determined by an electronic device (101) within a location associated with an event for the use of Wi-Fi (wireless fidelity). Within the environment (700), the location of the electronic device (101) may change from location (701) through location (703) to location (705) according to the movement of the user. The location of the electronic device (101) may change from location (701) to location (703) through a movement path (702). The location of the electronic device (101) may change from location (703) to location (705) through a movement path (704).

[0143] According to one embodiment, the electronic device (101) may use an inertial measurement unit (IMU) sensor (e.g., at least one sensor (170)) to identify coordinates for the position of the electronic device (101). For example, the electronic device (101) may perform an estimation of the position change of the electronic device (101) by using at least one sensor among an accelerometer sensor, a gyroscope, and a magnetometer sensor. For example, the electronic device (101) may calculate the distance traveled and / or direction of travel of the electronic device (101) and obtain coordinate information for the position by measuring the linear acceleration of the electronic device (101) through the accelerometer sensor and measuring the rotational angular velocity of the electronic device (101) through the gyroscope.

[0144] According to one embodiment, at a location (701), the electronic device (101) can identify coordinates (x1, y1, z1) for the position of the electronic device (101) through at least one sensor (170). At a location (701), the electronic device (101) can identify the received signal strength indicator (RSSI) of a first wireless communication signal received from the AP device (711) as a first value (e.g., -70 (dBm (decibel-milliwatts))). At a location (701), the electronic device (101) can identify the distance (d1) between the position of the electronic device (101) and / or the position of the AP device (701) according to the RSSI of the first wireless communication signal.

[0145] According to one embodiment, at position (703), the electronic device (101) can identify coordinates (x2, y2, z2) for the position of the electronic device (101) through at least one sensor (170). At position (703), the electronic device (101) can identify the received signal strength indicator (RSSI) of a second wireless communication signal received from the AP device (711) as a second value (e.g., -32 (dBm)). At position (703), the electronic device (101) can identify the distance (d2) between the position of the electronic device (101) and / or the position of the AP device (701) according to the RSSI of the second wireless communication signal.

[0146] According to one embodiment, at a location (705), the electronic device (101) can identify coordinates (x3, y3, z3) for the position of the electronic device (101) through at least one sensor (170). At a location (705), the electronic device (101) can identify the received signal strength indicator (RSSI) of a third wireless communication signal received from the AP device (711) as a third value (e.g., -41 (dBm)). At a location (705), the electronic device (101) can identify the distance (d3) between the position of the electronic device (101) and / or the position of the AP device (701) according to the RSSI of the third wireless communication signal.

[0147] According to one embodiment, the electronic device (101) can determine the coordinates (x4, y4, z4) of the location of the AP device (711) defined for the electronic device (101) based on positioning for the AP device (711) using coordinates (x1, y1, z1) for location (701), coordinates (x2, y2, z2) for location (703), coordinates (x3, y3, z3) for location (705), distance (d1), distance (d2), and / or distance (d3). For example, the positioning may be performed based on trilateration. For example, the electronic device (101) may provide information to guide the user to move based on identifying that the location of the electronic device (101) and / or the distance between the location of the electronic device (101) and the location of the AP device (711) is additionally required for the positioning of the AP device (711).

[0148] According to one embodiment, the electronic device (101) can identify the location of the electronic device (101) through at least one sensor (170) even if no signal for a global positioning system (GPS) is received within the location associated with the event.

[0149] According to one embodiment, the first wireless communication signal, the second wireless communication signal, and / or the third wireless communication signal may be received sequentially through the electronic device (101), either periodically or non-periodically, while a change in the position of the electronic device (101) is detected through at least one sensor (170).

[0150] According to one embodiment, the electronic device (101) can determine the location of the AP device (711) using a wireless communication signal received before the event is identified.

[0151] Figure 8 is an example of an environment in which the location of a candidate spot for Wi-Fi use is determined based on image data acquired through a camera of an electronic device.

[0152] According to one embodiment, with reference to FIG. 8, an environment (800) is shown in which the locations of candidate spots defined for an electronic device (101) and / or an AP device (711) are determined within a location associated with an event for the use of Wi-Fi (wireless fidelity). Within the environment (800), each of the spots (811), spots (812), and spots (813) may be located within the location associated with the event. Each of the spots (811), spots (812), and spots (813) may be described as candidate spots for the use of Wi-Fi.

[0153] According to one embodiment, the electronic device (101) can identify the location of each of the candidate spots (e.g., spot (811), spot (812), and / or spot (813)) defined for the electronic device (101) using image data obtained through the camera (130).

[0154] According to one embodiment, the electronic device (101) can obtain a depth map from the image data that indicates the depth of a spot (813) included in the image data. For example, the electronic device (101) can identify the distance (d4) between a location (705) and a location of a spot (813) based on the obtained depth map.

[0155] According to one embodiment, the electronic device (101) can identify an angle (θ) between the AP device (711) and the spot (813), defined for a location (705), based on image data obtained through the camera (130) and / or coordinates (x4, y4, z4) for the location of the AP device (711). For example, the electronic device (101) can identify the angle (θ) using an accelerometer sensor (e.g., at least one sensor (170)).

[0156] According to one embodiment, the electronic device (101) can identify the distance (d5) between the location of the spot (813) and the location of the AP device (711) based on the distance (d3), distance (d4), and / or angle (θ).

[0157] According to one embodiment, the electronic device (101) can determine the estimated throughput when accessing the AP device (711) from the spot (813) according to the distance (d5). The estimated throughput may decrease as the distance (d5) increases. For example, the electronic device (101) can determine the estimated throughput when accessing the wireless access node device (711) from the spot (813) by applying the distance (d5) obtained based on scene understanding data and / or RSSI (received signal strength indicator) measurements to an AI (artificial intelligence) model (e.g., the fourth trained model (406) of FIG. 4).

[0158] Figure 9 is an example of an environment for determining the estimated throughput when accessing an AP device from a candidate spot based on the attributes of obstacles within the communication path for accessing an AP device from a candidate spot for Wi-Fi use.

[0159] According to one embodiment, with reference to FIG. 9, an environment (900) is illustrated in which an obstacle (901) exists in a communication path for accessing an AP device (711) at spot (813) among spot (811), spot (812), and / or spot (813) within a location associated with an event for the use of Wi-Fi (wireless fidelity). At location (705), an electronic device (101) can acquire image data including the obstacle (901) within the field of view (902) of a camera (130).

[0160] According to one embodiment, the electronic device (101) can identify path information regarding whether the communication path for accessing the AP device (711) at the spot (813) corresponds to LOS (line of sight) or NLOS (non-line of sight) using the image data.

[0161] According to one embodiment, the electronic device (101) can identify that the communication path corresponds to NLOS based on identifying an obstacle (901) present within the communication path. For example, the electronic device (101) can correct the estimated value of the throughput (or communication quality) by using a pre-trained model to estimate the throughput (or communication quality) based on the communication path corresponding to NLOS.

[0162] According to one embodiment, the electronic device (101) can determine the estimated throughput when accessing the AP device (711) at the spot (813) according to the path information. The throughput estimated according to the path information corresponding to LOS may be greater than the throughput estimated according to the path information corresponding to NLOS.

[0163] According to one embodiment, the electronic device (101) can identify material information and / or size information regarding an obstacle (901) using the image data. For example, the material information may include information about the material (e.g., brick, glass, wood, plastic, and / or concrete) of the obstacle (901) present in the communication path. For example, the size information may include information about the width and / or thickness of the obstacle (901) present in the communication path. The electronic device (101) can determine the estimated throughput when accessing the AP device (711) at the spot (813) based on the material information and / or the size information.

[0164] According to one embodiment, the electronic device (101) can identify the distance (d6) between the obstacle (901) and the AP device (711) using the image data. For example, the estimated throughput may decrease as the distance (d6) decreases.

[0165] Figure 10 is a graph illustrating the throughput determined by the properties of obstacles within the communication path for accessing an AP device at a candidate spot location for Wi-Fi use.

[0166] According to one embodiment, with reference to FIG. 10, a graph (1000) showing a transmission coefficient according to the material and / or thickness of an obstruction in a communication path is shown.

[0167] According to one embodiment, in the graph (1000), the x-axis represents the thickness of the obstacle, and the y-axis represents the transmission coefficient of the electromagnetic wave to the obstacle.

[0168] According to one embodiment, the transmission coefficient may have a positive correlation with the estimated throughput when accessing an AP device at a candidate spot for Wi-Fi use. Referring to the graph (1000), it can be seen that the estimated throughput decreases as the thickness of the obstacle increases.

[0169] According to one embodiment, in the graph (1000), each of the materials (1001), material (1002), material (1003), material (1004), and material (1005) represents a different material of obstacle. For example, material (1001) may represent brick, material (1002) may represent concrete, material (1003) may represent glass, material (1004) may represent wood, and material (1005) may represent plastic. By referring to the graph (1000), it can be seen that the estimated throughput is determined by the material of the obstacle.

[0170] FIG. 11 is an example of an environment in which the estimated throughput is determined when accessing an AP device from a candidate spot based on interference from external electronic devices around a candidate spot for Wi-Fi use.

[0171] According to one embodiment, with reference to FIG. 11, an environment (1100) is shown in which a user (1101) using an external electronic device (1102) is present around spot (812) among spot (811), spot (812), and / or spot (813) within a location associated with an event for the use of Wi-Fi (wireless fidelity). At location (705), the electronic device (101) can acquire image data including the external electronic device (1102) within the field of view (1103) of the camera (130).

[0172] According to one embodiment, the electronic device (101) can identify interference information indicating that an external electronic device (1102) is present around the spot (812) based on the image data.

[0173] According to one embodiment, the electronic device (101) can determine the estimated throughput when accessing the AP device (711) at the spot (812) according to the interference information. For example, the throughput estimated according to interference information indicating that no external electronic device is present may be greater than the throughput estimated according to interference information indicating that an external electronic device is present.

[0174] FIGS. 12a and 12b illustrate examples of environments that visually display recommended spots for Wi-Fi use based on events for Wi-Fi use within an electronic device.

[0175] According to one embodiment, with reference to FIG. 12a, an environment (1200a) is shown in which an image (1202) of augmented reality (AR) is displayed through at least one display (140) while an electronic device (101), which is a head-wearable electronic device, is worn by a user (1201). The image (1202) may include a spot (811), a spot (812), and / or a spot (813) identified as candidate spots for Wi-Fi use.

[0176] According to one embodiment, the electronic device (101) can determine, based on an event for the use of Wi-Fi, an estimated throughput when accessing the AP device at a spot (811), an estimated throughput when accessing the AP device at a spot (812), and / or an estimated throughput when accessing the AP device at a spot (813).

[0177] According to one embodiment, the electronic device (101) can identify the spot (811) as a remaining candidate spot based on the fact that the estimated throughput when accessing the AP device at the spot (811) is within a first range.

[0178] According to one embodiment, the electronic device (101) can identify the spot (812) as a remaining candidate spot based on the fact that the estimated throughput when accessing the AP device at the spot (812) is within the first range.

[0179] According to one embodiment, the electronic device (101) can identify the spot (813) as a recommended spot for guiding Wi-Fi usage based on the fact that the estimated throughput when accessing the AP device at the spot (813) is within a second range greater than the first range.

[0180] According to one embodiment, the electronic device (101) may display the spot (813) in an image (1202) displayed through at least one display (140) with the spot (813) visually highlighted relative to the spot (811) and / or spot (812) to guide access to the AP device at the spot (813), based on identifying the spot (813) among the spots (811), spot (812), and / or spot (813) to guide access to the AP device at the spot (813). For example, the electronic device (101) may display a visual effect (1203) to guide access to the AP device at the spot (813) through at least one display (140) at a location in the image (1202) corresponding to the spot (813).

[0181] According to one embodiment, with reference to FIG. 12b, an environment (1200b) is shown in which an image (1202) is displayed through at least one display (140) of an electronic device (101) which is a smartphone. The image (1202) may include a spot (811), a spot (812), and / or a spot (813) identified as candidate spots for Wi-Fi use.

[0182] According to one embodiment, the electronic device (101) can determine, based on an event for the use of Wi-Fi, an estimated throughput when accessing the AP device at a spot (811), an estimated throughput when accessing the AP device at a spot (812), and / or an estimated throughput when accessing the AP device at a spot (813).

[0183] According to one embodiment, the electronic device (101) can identify the spot (811) as a remaining candidate spot based on the fact that the estimated throughput when accessing the AP device at the spot (811) is within a first range.

[0184] According to one embodiment, the electronic device (101) can identify the spot (812) as a remaining candidate spot based on the fact that the estimated throughput when accessing the AP device at the spot (812) is within the first range.

[0185] According to one embodiment, the electronic device (101) can identify the spot (813) as a recommended spot for guiding Wi-Fi usage based on the fact that the estimated throughput when accessing the AP device at the spot (813) is within a second range greater than the first range.

[0186] According to one embodiment, the electronic device (101) may display the spot (813) in an image (1202) displayed through at least one display (140) with the spot (813) visually highlighted relative to the spot (811) and / or spot (812) to guide access to the AP device at the spot (813), based on identifying the spot (813) among the spots (811), spot (812), and / or spot (813) to guide access to the AP device at the spot (813). For example, the electronic device (101) may display a visual effect (1203) to guide access to the AP device at the spot (813) through at least one display (140) at a location in the image (1202) corresponding to the spot (813). For example, the visual effect (1203) may indicate the level of throughput estimated when accessing the AP device at the spot (813). For example, while the electronic device (101) displays a visual effect (1203) through at least one display (140), it may provide the user with text and / or voice indicating the grounds (e.g., context information or obstacle information) on which spot (813) among spot (811), spot (812), and / or spot (813) was determined to be a recommended spot.

[0187] FIG. 12c illustrates an example of an environment in which information about recommended spots for Wi-Fi use is provided through a speaker based on an event for Wi-Fi use within an electronic device.

[0188] According to one embodiment, referring to FIG. 12c, an environment (1200c) in which a scene of the real world (1210) is displayed is shown while the electronic device (101), which is a head-wearable electronic device (e.g., the electronic device (101) shown in FIG. 2c), is worn by a user (1201). The scene (1202) may include a spot (811), a spot (812), and / or a spot (813) identified as candidate spots for Wi-Fi use.

[0189] According to one embodiment, the electronic device (101) can determine, based on an event for the use of Wi-Fi, an estimated throughput when accessing the AP device at a spot (811), an estimated throughput when accessing the AP device at a spot (812), and / or an estimated throughput when accessing the AP device at a spot (813).

[0190] According to one embodiment, the electronic device (101) can identify the spot (811) as a remaining candidate spot based on the fact that the estimated throughput when accessing the AP device at the spot (811) is within a first range.

[0191] According to one embodiment, the electronic device (101) can identify the spot (812) as a remaining candidate spot based on the fact that the estimated throughput when accessing the AP device at the spot (812) is within the first range.

[0192] According to one embodiment, the electronic device (101) can identify the spot (813) as a recommended spot for guiding Wi-Fi usage based on the fact that the estimated throughput when accessing the AP device at the spot (813) is within a second range greater than the first range.

[0193] According to one embodiment, the electronic device (101) may output information (1211) for guiding access to an AP device at a spot (813) through a speaker (160), based on identifying a spot (813) among a spot (811), a spot (812), and / or a spot (813) for guiding the use of Wi-Fi. For example, when the electronic device (101) provides the information (1211) as voice guide information, it may determine an image containing the recommended spot (813) among images acquired through a camera (130). For example, the electronic device (101) may identify an area in the determined image where the recommended spot (813) is displayed. For example, the electronic device (101) may perform image captioning using an artificial intelligence (AI) model (e.g., an image representation AI model or an image to text AI model) for outputting a description or caption of the area. For example, the electronic device (101) may generate guide text for accessing the AP device based on result information of the image captioning, estimated throughput information at the spot (813) corresponding to the recommended spot, and / or context information about the user. For example, the electronic device (101) may provide the guide text to the user through at least one display (140) or speaker (160).

[0194] FIG. 13 is an example of an environment that provides information about recommended spots in a space where multiple AP devices exist based on an event for the use of Wi-Fi within an electronic device.

[0195] According to one embodiment, with reference to FIG. 13, a user environment (1300) is shown in which a user wearing and / or carrying an electronic device (101) uses the electronic device (101) within a location (1310) associated with an event for the use of Wi-Fi (wireless fidelity). Within the environment (1300), the location of the electronic device (101) may change from location (1301) through location (1302) to location (1303) according to the user's movement. At location (1302), the electronic device (101) can acquire image data corresponding to the field of view (1304) of the camera (130). At location (1303), the electronic device (101) can acquire image data corresponding to the field of view (1305) of the camera (130).

[0196] According to one embodiment, the place (1310) may be described as a place (e.g., a coffee shop) where an access point (AP) device (1321) and / or an AP device (1322) is located, which provides a wireless network for wireless fidelity (Wi-Fi) to surrounding electronic devices. For example, the AP device may be described as a hub of a wired LAN connecting a wired network and a wireless network.

[0197] According to one embodiment, the place (1310) may have a spot (1311), a spot (1312), and / or a spot (1313) for a user using Wi-Fi through an electronic device (101). By example, without limitation, each of the spot (1311), spot (1312), and spot (1313) may be described as a spot where a table located within the place (1310) is located.

[0198] According to one embodiment, at a location (1302), an electronic device (101) can identify an event for the use of Wi-Fi based on user input (1331) for using Wi-Fi through the electronic device (101) within a place (1310). For example, user input (1331) may be described as voice input by a user and / or touch input (e.g., text input) for at least one display (130). For example, the electronic device (101) may, in response to user input (1331), determine the estimated throughput when accessing the AP device (1321) from the spot (1311) as a first value (e.g., -38 (dBm (decibel-milliwatts))) and the estimated throughput when accessing the AP device (1322) from the spot (1311) as a second value (e.g., -72 (dBm)). For example, the electronic device (101) may identify that the estimated throughput when accessing the AP device (1321) from the spot (1311) is greater than that of the AP device (1322) based on the determination of the first value and the second value. The electronic device (101) may output a response (1332) for the user input (1331) through the speaker (160). For example, The response (1332) can be described as a response to suggest a spot (1311) located next to the window (1341) as a recommended spot to guide the use of Wi-Fi.

[0199] According to one embodiment, at a location (1303), an electronic device (101) can identify an event for the use of Wi-Fi based on a user input (1333) for changing a candidate spot indicated by a response (1332). For example, the user input (1333) may be described as a user's voice input and / or touch input (e.g., text input) for at least one display (140). For example, in response to the user input (1333), the electronic device (101) may determine a third value (e.g., -70 (dBm)) for the estimated throughput when accessing the AP device (1321) from the spot (1313) and a fourth value (e.g., -31 (dBm)) for the estimated throughput when accessing the AP device (1322) from the spot (1313). For example, the electronic device (101) can identify, based on the determination of the third value and the fourth value, that the estimated throughput when accessing the AP device (1322) from the spot (1313) is greater than that of the AP device (1321). The electronic device (101) can output a response (1334) for user input (1333) through the speaker (160). For example, the response (1334) may be described as a response to suggest a recommended spot to guide the use of Wi-Fi through the AP device (1322) at the spot (1313) located next to the spot (1312) occupied by the human (1314) and / or human (1315).

[0200] FIG. 14 is a flowchart illustrating a method for providing information corresponding to a recommended spot based on the estimation of the predicted communication quality for a wireless access node device at a candidate spot.

[0201] According to one embodiment, with reference to FIG. 14, in operation 1401, at least one processor (110) can obtain first information corresponding to a wireless access node device located within a wireless communication range with the electronic device (101) through a communication circuit (180) (or a wireless communication circuit).

[0202] According to one embodiment, at least one processor (110) can obtain a relative position of the electronic device (101) of the wireless access node device as at least part of the first information through the wireless communication circuit. For example, at least one processor (110) can perform the operation of obtaining the relative position based on at least part of the first data, the second data, and the third data. For example, the first data may correspond to a first wireless communication signal received from the wireless access node device when the electronic device (101) is located at a first position. For example, the second data may correspond to a second wireless communication signal received from the wireless access node device when the electronic device (101) is located at a second position different from the first position. For example, the third data may correspond to a third wireless communication signal received from the wireless access node device when the electronic device (101) is located at a third position different from the first position and the second position. For example, the electronic device (101) may perform the operation of obtaining the relative position based further on the fourth data corresponding to the movement identified through at least one sensor (170) for tracking the movement of the user of the electronic device (101).

[0203] According to one embodiment, in operation 1402, at least one processor (110) can obtain second information corresponding to candidate spots close to the electronic device (101) based at least part of an image corresponding to the surroundings of the electronic device (101) obtained through a camera (130).

[0204] According to one embodiment, at least one processor (110) can determine (or identify) the distance between the candidate spot and the electronic device (101) as at least part of the second information based on at least part of the image. For example, at least one processor (110) can obtain the angle between the wireless access node device and the candidate with respect to the electronic device (101). For example, at least one processor (110) can perform the operation of estimating the predicted communication quality based on at least part of the relative position, the distance, and the angle.

[0205] According to one embodiment, in operation 1403, at least one processor (110) can estimate a predicted communication quality (e.g., estimated throughput) for the wireless access node device at the candidate spot based on at least some of the first information and the second information.

[0206] According to one embodiment, at least one processor (110) may receive voice input from a user of an electronic device (101) through a microphone (150). For example, if the text corresponding to the voice input does not contain words related to wireless communication, at least one processor (110) may identify at least a portion of the voice input as a request for information corresponding to a recommended spot for performing wireless communication (e.g., third information to be described later), based on at least a portion of context information related to the voice input. For example, at least one processor (110) may use at least one of the following as at least a portion of the context information for the identification of the request: information corresponding to the location where the electronic device (101) is located, usage history information (or past history information) for a designated application at said location, and activity information related to said location obtained based on said image. For example, the above activity information can be described as information indicating the behavior of other users within a location associated with an event for using Wi-Fi.

[0207] According to one embodiment, the wireless access node device may include a first wireless access node device and a second wireless access node device. For example, at least one processor (110) may select one of the first wireless access node device and the second wireless access node device as a target wireless access node device. For example, at least one processor (110) may perform the operation of estimating the predicted communication quality for the target wireless access node device. For example, the first wireless access node device may correspond to a first SSID (service set identifier). For example, the second wireless access node device may correspond to a second SSID. For example, at least one processor (110) may select the first wireless access node device as the target wireless access node device based at least partially on identifying that the first SSID contains text corresponding to the location where the electronic device (101) is located, and the second SSID does not contain said text.

[0208] According to one embodiment, at least one processor (110) can determine whether the wireless access node device is in a non-line of sight environment with respect to the candidate spot based on information corresponding to an object between the wireless access node device and the candidate spot identified from the image. For example, if the at least one processor (110) determines that the wireless access node device is in the non-line of sight environment with respect to the candidate spot, the predicted communication quality can be lowered.

[0209] According to one embodiment, the candidate spot may include a first candidate spot having a first predicted communication quality and a second candidate spot having a second predicted communication quality lower than the first predicted communication quality. For example, at least one processor (110) may select the first candidate spot as the recommended spot. For example, at least one processor (110) may select the second candidate spot instead of the first candidate spot as the recommended spot based further on context information related to the input of a user of the electronic device (101). For example, at least one processor (110) may confirm (or identify) at least one of the user's preference for the surrounding environment of the spot analyzed from the image, the user's expected activity, or device information corresponding to another electronic device being used by the user, as at least part of the context information.

[0210] According to one embodiment, in operation 1404, at least one processor (110) may provide third information corresponding to a recommended spot to perform wireless communication through the wireless access node device based at least part of the predicted communication quality.

[0211] According to one embodiment, at least one processor (110) may generate text describing the recommended spot as at least part of the third information. For example, at least one processor (110) may output the converted text as voice through a speaker (160) included in the electronic device (101) or an external speaker (e.g., Bluetooth earphones) functionally connected to the electronic device (101).

[0212] According to one embodiment, at least one processor (110) can display a preview image obtained using a camera (130) as the image through at least one display (140). For example, at least one processor (110) can display information regarding the recommended spot together with the preview image through at least one display (140) as at least part of the third information, in association with the image spot corresponding to the recommended spot among the preview image. For example, the candidate spot may include a first candidate spot and a second candidate spot. For example, at least one processor (110) can display a first indication representing a first image spot corresponding to the first candidate spot among the preview image and a second indication representing a second image spot corresponding to the second candidate spot so as to overlap at least partially with the preview image. For example, at least one processor (110) can display information regarding the recommendation spot through at least one display (140) such that one indication corresponding to the recommendation spot among the first indication and the second indication is visually emphasized more than another indication among the first image spot and the second image spot.

[0213] According to one embodiment, at least one processor (110) can recognize at least one of an access point (AP) of a Wi-Fi (wireless fidelity) network and a base station of a cellular network as the wireless communication access node device.

[0214] According to one embodiment, the electronic device (101) can maximize the convenience of a user of Wi-Fi by providing information on at least one recommended spot to guide access to an AP device among candidate spots for Wi-Fi use within a place associated with an event for Wi-Fi use.

[0215] However, the present disclosure is not limited thereto. According to one embodiment, the electronic device (101) may provide information about candidate spots for the installation of an AP device. An operation method for providing information about candidate spots for the installation of an AP device is described below with reference to FIGS. 15a and 15b. In one embodiment, the electronic device (101) may provide information about the estimated throughput when accessing a base station at a user's destination. An operation method for providing information about the estimated throughput when accessing a base station is described later with reference to FIGS. 16a and 16b.

[0216] FIGS. 15a and FIGS. 15b are drawings illustrating an example of identifying candidate spots for the installation of an AP device.

[0217] According to one embodiment, with reference to FIG. 15a, an environment (1500a) for installing an AP device is illustrated. Within the environment (1500a), an electronic device (101) can acquire image data for an image (1510) through a camera (130). Based on the image data for the image (1510), the electronic device (101) can identify a spot (1511), a spot (1512), a spot (1513), a spot (1514), a spot (1515), and a spot (1516). For example, the electronic device (101) may identify spots (1511), spots (1512), spots (1513), spots (1514), spots (1515), and / or spots (1516) among spots (1511), spots (1512), spots (1513), spots (1514), and spots (1515) as spots that can be installed for the AP device based on user input for the installation of the AP device. For example, the electronic device (101) may identify spot (1516) among spots (1511), spots (1512), spots (1513), spots (1514), spots (1515), and / or spots (1516) as spots that cannot be installed for the AP device based on user input for the installation of the AP device. For example, the electronic device (101) may display visual information (1531) at a location corresponding to the spot (1512) through at least one display (140) to guide the installation of the AP device at the spot (1512). According to one embodiment, at least one processor (110) may provide information about the installation of the wireless access node device and / or the location of the hot spot at a specific location in response to a query from a user of the electronic device (101) using a trained model (e.g., the fourth trained model (406) of FIG. 4) trained to estimate communication quality.

[0218] According to one embodiment, at least one processor (110) can obtain scene understanding data from an image obtained through a camera (130) based on a user's query.

[0219] According to one embodiment, at least one processor (110) can extract keywords from a user's query. By example, without limitation, the extracted keywords may be associated with recommendations for installation locations of wireless access node devices, wireless access node devices owned by the user, and / or whether the user has moved. For example, at least one processor (110) can generate a prompt corresponding to the user's query based on the extracted keywords.

[0220] According to one embodiment, at least one processor (110) can identify a target object and / or a target spot (e.g., spot (1511), spot (1512), spot (1513), spot (1514), spot (1515), and / or spot (1516)) within a scene associated with a user's query by using a model trained to estimate communication quality (e.g., the fourth trained model (406) of FIG. 4) based on a generated prompt. For example, at least one processor (110) can determine at least one sub-AI agent (e.g., the model trained to estimate communication quality) among sub-AI agents (504 of FIG. 5) to respond to the user's query by using a multi-AI agent (503 of FIG. 5).

[0221] According to one embodiment, at least one processor (110) can determine a target spot without a weak electric field as the final target spot by estimating the relative communication quality between target spots using a model trained to estimate communication quality. For example, at least one processor (110) can provide information about the determined final target spot among the target spots.

[0222] According to one embodiment, at least one processor (110) can display an AP device owned by a user for a final target spot through at least one display (140).

[0223] According to one embodiment, with reference to FIG. 15b, an example of a user interface (1500b) that provides a response to user input for the installation of an AP device is illustrated. For example, at least one processor (110) may display user input (1521) for the installation of an AP device through at least one display (140). For example, at least one processor (110) may display a response (1522) obtained based on the user input (1521) through at least one display (140). For example, the response (1522) may be described as a response for querying information required for the installation of an AP device. For example, at least one processor (110) may display user input (1523) containing information required for the installation of an AP device through at least one display (140). For example, at least one processor (110) can display a response (1524) obtained based on user input (1523) through at least one display (140). For example, the response (1524) can be described as a response for suggesting spot (1514) among spot (1511), spot (1512), spot (1513), spot (1514), and spot (1515) shown in FIG. 15a as a spot for guiding the installation of an AP device.

[0224] FIGS. 16a and FIGS. 16b are drawings to illustrate an example of providing information on the estimated throughput when accessing a base station at a user's destination.

[0225] According to one embodiment, with reference to FIG. 16a, an environment (1600a) is shown that provides information on the estimated throughput when accessing a base station at a user's destination. The environment (1600a) may include a building (1601), a building (1602), and a user's destination (1605). A base station (1603) may be located in the building (1601). A user may move from location (1611) to location (1614) via location (1612) and location (1613). Location (1614) may be described as a location corresponding to a destination (1605) identified by map application software executed by at least one processor (110). An electronic device (101) may provide information on the estimated throughput when accessing a base station (1603) at a destination (1605) before the user reaches location (1614). For example, the electronic device (101) may provide information indicating an unstable network state at a destination (1605) based on identifying that a communication path (1604) for accessing a base station (1603) at a location (1613) corresponds to a non-line of sight (NLOS).

[0226] According to one embodiment, with reference to FIG. 16b, a flowchart illustrating a method for providing information on the estimated throughput when accessing a base station at a user's destination is shown.

[0227] According to one embodiment, in operation 1621, at least one processor (110) can identify the user's destination (1605) using map application software while the user is using the network through the base station (1603).

[0228] According to one embodiment, in operation 1622, at least one processor (110) can determine the location of the base station (1603) based on the strength of signals received from the base station (1603) and the locations of the electronic device (101). For example, at location (1611), at least one processor (110) can identify a first distance based on the received signal strength indicator (RSSI) of the first signal received from the base station (1603) and a first location of the electronic device (101) detected through at least one sensor (170). For example, at location (1612), at least one processor (110) can identify a second distance based on the received signal strength indicator (RSSI) of the second signal received from the base station (1603) and a second location of the electronic device (101) detected through at least one sensor (170). For example, at a location (1613), at least one processor (110) can identify a third distance based on the RSSI of a third signal received from a base station (1603) and a third location of an electronic device (101) detected through at least one sensor (170). For example, at least one processor (110) can determine the location of the base station (1603) defined for the electronic device (101) based on positioning for the base station (1603) using the first location, the second location, the third location, the first distance, the second distance, and the third distance. For example, the positioning can be performed based on trilateration, which identifies the value of the target coordinate according to three or more reference coordinates and the distances between the reference coordinates and the target coordinate.

[0229] According to one embodiment, in operation 1623, at least one processor (110) can acquire image data through a camera (130). For example, at least one processor (110) can identify the direction in which the electronic device (101) is moved using the image data.

[0230] According to one embodiment, in operation 1624, at least one processor (110) can determine the estimated throughput when accessing the base station (1603) at a location (1614) corresponding to the destination (1605), based on the location of the base station (1603) and the image data.

[0231] According to one embodiment, in operation 1625, at least one processor (110) may provide information about the estimated throughput through at least one display (140) or speaker (160) when the location of the electronic device (101) corresponds to a location (1614) corresponding to a destination (1605).

[0232] According to one embodiment, the electronic device (101) may correspond to the electronic device (1701) described with reference to FIG. 17 below.

[0233] FIG. 17 is a block diagram of an electronic device in a network environment according to various embodiments.

[0234] According to one embodiment, with reference to FIG. 17, in a network environment (1700), an electronic device (1701) may communicate with an electronic device (1702) through a first network (1798) (e.g., a short-range wireless communication network) or with at least one of an electronic device (1704) or a server (1708) through a second network (1799) (e.g., a long-range wireless communication network). According to one embodiment, the electronic device (1701) may communicate with the electronic device (1704) through a server (1708). According to one embodiment, the electronic device (1701) may include a processor (1720), memory (1730), input module (1750), sound output module (1755), display module (1760), audio module (1770), sensor module (1776), interface (1777), connection terminal (1778), haptic module (1779), camera module (1780), power management module (1788), battery (1789), communication module (1790), subscriber identification module (1796), or antenna module (1797). In some embodiments, at least one of these components (e.g., connection terminal (1778)) may be omitted from the electronic device (1701), or one or more other components may be added. In some embodiments, some of these components (e.g., sensor module (1776), camera module (1780), or antenna module (1797)) may be integrated into a single component (e.g., display module (1760)).

[0235] According to one embodiment, the processor (1720) can control at least one other component (e.g., a hardware or software component) of the electronic device (1701) connected to the processor (1720) by executing software (e.g., a program (1740)), and can perform various data processing or operations. According to one embodiment, as at least part of the data processing or operations, the processor (1720) can store commands or data received from other components (e.g., a sensor module (1776) or a communication module (1790)) in a volatile memory (1732), process the commands or data stored in the volatile memory (1732), and store the resulting data in a non-volatile memory (1734). According to one embodiment, the processor (1720) may include a main processor (1721) (e.g., a central processing unit or an application processor) or an auxiliary processor (1723) that can operate independently or together with it (e.g., a graphics processing unit, a neural processing unit (NPU), an image signal processor, a sensor hub processor, or a communication processor). For example, if the electronic device (1701) includes a main processor (1721) and an auxiliary processor (1723), the auxiliary processor (1723) may be configured to use less power than the main processor (1721) or to be specialized for a specified function. The auxiliary processor (1723) may be implemented separately from the main processor (1721) or as part thereof.

[0236] According to one embodiment, the auxiliary processor (1723) may control at least some of the functions or states associated with at least one component of the electronic device (1701) (e.g., display module (1760), sensor module (1776), or communication module (1790)) on behalf of the main processor (1721) while the main processor (1721) is in an inactive (e.g., sleep) state, or together with the main processor (1721) while the main processor (1721) is in an active (e.g., application execution) state. According to one embodiment, the auxiliary processor (1723) (e.g., image signal processor or communication processor) may be implemented as part of another functionally related component (e.g., camera module (1780) or communication module (1790)). According to one embodiment, the auxiliary processor (1723) (e.g., neural network processing unit) may include a hardware structure specialized for processing an artificial intelligence model. The artificial intelligence model may be generated through machine learning. Such learning may be performed, for example, on the electronic device (1701) itself where the artificial intelligence model is executed, or through a separate server (e.g., server (1708)). The learning algorithm may 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 may include a plurality of artificial neural network layers.An artificial neural network may be 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 the hardware structure, the artificial intelligence model may include a software structure, either additionally or substantially.

[0237] According to one embodiment, the memory (1730) may store various data used by at least one component of the electronic device (1701) (e.g., a processor (1720) or a sensor module (1776)). The data may include, for example, input data or output data for software (e.g., a program (1740)) and related instructions. The memory (1730) may include volatile memory (1732) or non-volatile memory (1734).

[0238] According to one embodiment, the program (1740) may be stored as software in memory (1730) and may include, for example, an operating system (1742), middleware (1744), or an application (1746).

[0239] According to one embodiment, the input module (1750) may receive commands or data to be used by a component of the electronic device (1701) (e.g., processor (1720)) from outside the electronic device (1701) (e.g., user). The input module (1750) may include, for example, a microphone, a mouse, a keyboard, a key (e.g., a button), or a digital pen (e.g., a stylus pen).

[0240] According to one embodiment, the sound output module (1755) may output an audio signal to the outside of the electronic device (1701). The sound output module (1755) may include, for example, a speaker or a receiver. The speaker may be used for general purposes, such as multimedia playback or recording playback. The receiver may be used to receive incoming calls. According to one embodiment, the receiver may be implemented separately from the speaker or as part thereof.

[0241] According to one embodiment, the display module (1760) may visually provide information to an external (e.g., user) of the electronic device (1701). The display module (1760) may include, for example, a display, a holographic device, or a projector and a control circuit for controlling said device. According to one embodiment, the display module (1760) may include a touch sensor configured to detect a touch, or a pressure sensor configured to measure the intensity of the force generated by said touch.

[0242] According to one embodiment, the audio module (1770) may convert sound into an electrical signal or, conversely, convert an electrical signal into sound. According to one embodiment, the audio module (1770) may acquire sound through an input module (1750) or output sound through an audio output module (1755) or an external electronic device (e.g., electronic device (1702)) (e.g., speaker or headphones) connected directly or wirelessly to the electronic device (1701).

[0243] According to one embodiment, the sensor module (1776) may detect the operating state of the electronic device (1701) (e.g., power or temperature) or the external environmental state (e.g., user state) and generate an electrical signal or data value corresponding to the detected state. According to one embodiment, the sensor module (1776) may include, for example, a gesture sensor, a gyroscope sensor, a barometric pressure sensor, a magnetic sensor, an accelerometer sensor, a grip sensor, a proximity sensor, a color sensor, an IR (infrared) sensor, a biosensor, a temperature sensor, a humidity sensor, or an illuminance sensor.

[0244] According to one embodiment, the interface (1777) may support one or more specified protocols that can be used for the electronic device (1701) to be connected directly or wirelessly to an external electronic device (e.g., electronic device (1702)). According to one embodiment, the interface (1777) may include, for example, a high definition multimedia interface (HDMI), a universal serial bus (USB) interface, an SD card interface, or an audio interface.

[0245] According to one embodiment, the connection terminal (1778) may include a connector through which the electronic device (1701) can be physically connected to an external electronic device (e.g., electronic device (1702)). According to one embodiment, the connection terminal (1778) may include, for example, an HDMI connector, a USB connector, an SD card connector, or an audio connector (e.g., a headphone connector).

[0246] According to one embodiment, the haptic module (1779) can convert an electrical signal into a mechanical stimulus (e.g., vibration or movement) or an electrical stimulus that a user can perceive through tactile or kinesthetic senses. According to one embodiment, the haptic module (1779) may include, for example, a motor, a piezoelectric element, or an electric stimulation device.

[0247] According to one embodiment, the camera module (1780) can capture still images and video. According to one embodiment, the camera module (1780) may include one or more lenses, image sensors, image signal processors, or flashes.

[0248] According to one embodiment, the power management module (1788) can manage power supplied to the electronic device (1701). According to one embodiment, the power management module (1788) can be implemented, for example, as at least part of a power management integrated circuit (PMIC).

[0249] According to one embodiment, the battery (1789) can supply power to at least one component of the electronic device (1701). According to one embodiment, the battery (1789) may include, for example, a non-rechargeable primary battery, a rechargeable secondary battery, or a fuel cell.

[0250] According to one embodiment, the communication module (1790) may support the establishment of a direct (e.g., wired) communication channel or a wireless communication channel between an electronic device (1701) and an external electronic device (e.g., electronic device (1702), electronic device (1704), or server (1708)), and the performance of communication through the established communication channel. The communication module (1790) may include one or more communication processors that operate independently of the processor (1720) (e.g., application processor) and support direct (e.g., wired) communication or wireless communication. According to one embodiment, the communication module (1790) may include a wireless communication module (1792) (e.g., cellular communication module, short-range wireless communication module, or GNSS (global navigation satellite system) communication module) or a wired communication module (1794) (e.g., LAN (local area network) communication module, or power line communication module). The corresponding communication module among these communication modules can communicate with an external electronic device (1704) through a first network (1798) (e.g., a short-range communication network such as Bluetooth, WiFi (wireless fidelity) direct, or IrDA (infrared data association)) or a second network (1799) (e.g., 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 (1792) can identify or authenticate the electronic device (1701) within a communication network such as the first network (1798) or the second network (1799) using subscriber information (e.g., International Mobile Subscriber Identifier (IMSI)) stored in the subscriber identification module (1796).

[0251] According to one embodiment, the wireless communication module (1792) may support a 5G network following a 4G network and next-generation communication technology, for example, new radio access technology. The NR access technology may support high-speed transmission of high-capacity data (enhanced mobile broadband (eMBB)), minimization of terminal power and connection of multiple terminals (massive machine type communications (mMTC)), or high reliability and low latency (ultra-reliable and low-latency communications (URLLC)). The wireless communication module (1792) may support a high-frequency band (e.g., mmWave band) to achieve a high data transmission rate, for example. The wireless communication module (1792) can support various technologies for securing performance in the high-frequency band, such as beamforming, massive MIMO (multiple-input and multiple-output), full-dimensional MIMO (FD-MIMO), array antenna, analog beam-forming, or large-scale antenna. The wireless communication module (1792) can support various requirements specified in the electronic device (1701), external electronic device (e.g., electronic device (1704)), or network system (e.g., second network (1799)). According to one embodiment, the wireless communication module (1792) may support a Peak data rate (e.g., 20 Gbps or more) for eMBB realization, loss coverage (e.g., 164 dB or less) for mMTC realization, or U-plane latency (e.g., downlink (DL) and uplink (UL) each 0.5 ms or less, or round trip 1 ms or less) for URLLC realization.

[0252] According to one embodiment, the antenna module (1797) may transmit a signal or power to or from an external source (e.g., an external electronic device). According to one embodiment, the antenna module (1797) may include an antenna comprising a radiator made of a conductor or a conductive pattern formed on a substrate (e.g., a PCB). According to one embodiment, the antenna module (1797) 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 a first network (1798) or a second network (1799), may be selected from the plurality of antennas, for example, by a communication module (1790). The signal or power may be transmitted or received between the communication module (1790) and an external electronic device through the selected at least one antenna. According to some embodiments, in addition to the radiator, other components (e.g., a radio frequency integrated circuit (RFIC)) may be additionally formed as part of the antenna module (1797).

[0253] According to various embodiments, the antenna module (1797) 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 to a first surface (e.g., bottom surface) of the printed circuit board and capable of supporting a specified high frequency band (e.g., mmWave band), and a plurality of antennas (e.g., array antennas) disposed on or adjacent to a second surface (e.g., top surface or side surface) of the printed circuit board and capable of transmitting or receiving a signal of the specified high frequency band.

[0254] According to one embodiment, at least some of the components may be connected to each other via a communication method between peripheral devices (e.g., bus, GPIO (general purpose input and output), SPI (serial peripheral interface), or MIPI (mobile industry processor interface)) and may exchange signals (e.g., commands or data) with each other.

[0255] According to one embodiment, commands or data may be transmitted or received between an electronic device (1701) and an external electronic device (1704) through a server (1708) connected to a second network (1799). Each of the external electronic devices (1702, or 1704) may be the same or a different type of device as the electronic device (1701). According to one embodiment, all or part of the operations performed on the electronic device (1701) may be performed on one or more of the external electronic devices (1702, 1704, or 1708). For example, if the electronic device (1701) needs to perform a function or service automatically or in response to a request from a user or another device, the electronic device (1701) may request one or more external electronic devices to perform at least part of the function or service instead of performing the function or service itself or additionally. One or more external electronic devices that receive the above request may execute at least part of the requested function or service, or additional function or service related to the request, and transmit the result of the execution to the electronic device (1701). The electronic device (1701) may provide the result as is or additionally processed as at least part of the response to the request. For this purpose, for example, cloud computing, distributed computing, mobile edge computing (MEC), or client-server computing technology may be used. The electronic device (1701) may provide ultra-low latency services using, for example, distributed computing or mobile edge computing. In one embodiment, the external electronic device (1704) may include an Internet of Things (IoT) device. The server (1708) may be an intelligent server using machine learning and / or neural networks.According to one embodiment, an external electronic device (1704) or server (1708) may be included within the second network (1799). The electronic device (1701) may be applied to intelligent services (e.g., smart home, smart city, smart car, or healthcare) based on 5G communication technology and IoT-related technology.

[0256] FIG. 18 is a schematic diagram of an exemplary AI system according to one embodiment.

[0257] According to one embodiment, with reference to FIG. 18, an AI system (1800) may include an input / output interface (1810), an AI (artificial intelligence) framework (1820), a generative AI model (1830), an application / service component (1880), and / or a knowledge repository (1890).

[0258] According to one embodiment, an input / output interface (1810) may receive input. The input may include user input and / or data obtained or generated by an electronic device (e.g., the electronic device (101) or electronic device (1701) described above). The data may include images, videos, and / or sensor data generated by at least one processor of the electronic device (e.g., at least one processor (110) or processor (1720)), such as illuminance data around the electronic device obtained from a sensor or sensor hub (e.g., auxiliary processor (1723), attitude data (or orientation data) of the electronic device, temperature inside the electronic device (e.g., at least one display (140)) or temperature of at least one processor (110), size information of the display area of ​​the display, and / or images obtained through an image sensor of the electronic device (e.g., included in a camera module (1780)). The user input may include natural language, touch data obtained through a touch circuit included within the display panel (e.g., used to identify input from a finger and / or stylus), an image displayed (and / or to be displayed) on the display panel, and / or video. By example, without limitation, the user input may be received by an input / output interface (1810) along with context information. The context information may be described as additional information obtained in relation to the user input. The context information may be related to the state at the time the user input is received (e.g., the state of the electronic device and / or the state of the surroundings of the electronic device (e.g., user state)). For example, the context information may include information about one or more software applications executed within the electronic device at the time the user input is received.For example, the above situation information may include information about the location of the electronic device (or the location of the user of the electronic device) at the time the user input is received. For example, the user input may be integrated with the situation information. For example, the user input with the situation information integrated as the input may be received by the input / output interface (1810).

[0259] According to one embodiment, the input / output interface (1810) may transmit (or provide) an output. The output may include a result (or result information) generated or obtained by the AI ​​system (1800) based on at least part of the input. The format of the output may vary. For example, the output may include natural language. For example, the output may include content (e.g., media content and / or multimedia content). For example, the output may include an action related to the user of the electronic device. For example, the output may have a format according to the user settings of the electronic device.

[0260] According to one embodiment, the input / output interface (1810) can be described as a user question / response interface.

[0261] According to one embodiment, the AI ​​framework (1820) may be used to obtain information (or data) about the input from the input / output interface (1810) and to control one or more components related to the AI ​​system (1800) using the obtained information.

[0262] According to one embodiment, a prompt design component (1821) within an AI framework (1820) may generate or obtain prompts for a generative AI model (1830) (e.g., including a large language model (LLM) or a large multimodal model (LMM)) using the acquired information. For example, the prompt design component (1821) may be described as an AI component that utilizes a learning algorithm and / or a neural network to provide prompts that are enhanced over time. For example, the prompt design component (1821) may generate or obtain prompts by accessing a knowledge component (e.g., a knowledge repository (1890)) containing user preference data, a prompt library, and / or prompt examples using the acquired information. The generated prompts may be provided to the generative AI model (1830) (e.g., including an LLM or LMM).

[0263] According to one embodiment, an API / plugin management component (1822) within the AI ​​framework (1820) may be used to support communication for additional information requested (or induced) in relation to the prompt provided (or to be provided) to the generative AI model (1830). For example, the API / plugin management component (1822) may be used to create or establish a channel for communication with various data sources (e.g., knowledge repository (1890)). For example, the API / plugin management component (1822) may support access to at least some of the data sources. For example, the API / plugin management component (1822) may be used to request another component (e.g., application / service component (1880)) that performs feedback (or response) according to the prompt. As a non-limiting example, information obtained (or generated) through the API / plugin management component (1822) may be provided to the prompt design component (1821) for generating a prompt. As a non-limiting example, information obtained (or generated) through the API / plugin management component (1822) may be provided to the generative AI model (1830).

[0264] According to one embodiment, an improvement component (1823) within the AI ​​framework (1820) may at least partially tune (or adjust) (or change) the result (e.g., content) obtained (or output) from the generative AI model (1830). For example, the improvement component (1823) may determine or verify whether the content obtained from the generative AI model (1830) is related to the input. For example, the improvement component (1823) may determine or verify whether the content obtained from the generative AI model (1830) contains biased content. For example, the improvement component (1823) may determine or verify whether the content obtained from the generative AI model (1830) contains harmful content. For example, the improvement component (1823) may support or assist in performing additional processing to improve the content obtained from the generative AI model (1830). For example, the improvement component (1823) may support providing a hint to the user to improve the content.

[0265] According to one embodiment, the generative AI model (1830) may be described as an artificial intelligence neural network that generates feedback in response to a prompt. For example, the feedback may include additional data and / or information relative to the prompt, but relative to the prompt. For example, the feedback may include new content relative to the prompt. For example, the generative AI model (1830) may include a model that generates images and / or a model that generates language. For example, the model that generates images may include a generative adversarial network (GAN) and / or a variational autoencoder (VAE). For example, the model that generates images may include a diffusion-based generative model (e.g., a transformer VAE). For example, the model that generates language may include CHAT-GPT 3 and / or CHAT-GPT 4. For example, a generative AI model (1830) may include an LMM that generates the feedback by recognizing text, images, and / or speech.

[0266] According to one embodiment, as an example but not limited to, an AI framework (1820) and / or a generative AI model (1830) may be included within an AI module (e.g., including a processing circuit) within the electronic device. For example, the AI ​​module may be operatively coupled with at least one processor of the electronic device (e.g., at least one processor (110) or processor (1720)). For example, the AI ​​module may be operatively coupled with a display driving circuit of the electronic device. For example, the AI ​​module may be operatively coupled with a sensor hub of the electronic device for one or more sensors within the electronic device.

[0267] The technical problems to be solved in this disclosure are not limited to those mentioned above, and other technical problems not mentioned will be clearly understood by those skilled in the art to which this disclosure pertains.

[0268] As described above, an electronic device (e.g., electronic device (101)) may include a camera (e.g., camera (130)); a display (e.g., at least one display (140)); a communication circuit for Wi-Fi (wireless fidelity) (e.g., communication circuit (180)); at least one processor (e.g., at least one processor (110)) including a processing circuit; and a memory (e.g., memory (120)) that stores instructions and includes one or more storage media. The instructions, when executed individually or collectively by the at least one processor, include: identifying an event for Wi-Fi use; acquiring image data for an image to be displayed on the display, based on the event, through the camera; displaying the image through the display; identifying candidate spots for Wi-Fi use within a location associated with the event using the image data; and receiving wireless communication signals from a wireless access node device around the electronic device. Using the wireless communication signals and the image data, the location of each of the candidate spots defined for the wireless access node device and the electronic device is identified; based on the location of each of the candidate spots, at least one recommended spot among the candidate spots is identified; and the electronic device can be caused to display the at least one recommended spot within the image displayed through the display, with the recommendation spot being visually highlighted relative to at least one remaining candidate spot among the candidate spots, in order to guide access to the wireless access node device at the at least one recommended spot.

[0269] For example, when the above instructions are executed individually or collectively by the at least one processor, the electronic device may be caused to: determine the distance between the candidate spot and the wireless access node device based on the location of the candidate spot defined for the wireless access node device and the electronic device; determine the estimated throughput when accessing the wireless access node device from the candidate spot according to the distance, wherein the estimated throughput decreases as the distance increases; identify the candidate spot as the at least one recommended spot among the candidate spots based on the estimated throughput within a first range; and identify the candidate spot as the at least one remaining candidate spot among the candidate spots based on the estimated throughput within a second range smaller than the first range.

[0270] For example, when the above instructions are executed individually or collectively by the at least one processor, the electronic device may be caused to: identify, using the image data, path information regarding whether a communication path for accessing the wireless access node device from the candidate spot corresponds to a line of sight (LOS) or a non-line of sight (NLOS), based on the location of the candidate spot defined for the wireless access node device and the electronic device; determine, according to the path information, the estimated throughput when accessing the wireless access node device from the candidate spot, and the throughput estimated according to the path information corresponding to the LOS is greater than the throughput estimated according to the path information corresponding to the NLOS; identify the candidate spot as the at least one recommended spot among the candidate spots based on the estimated throughput within a first range; and identify the candidate spot as the at least one remaining candidate spot among the candidate spots based on the estimated throughput within a second range smaller than the first range.

[0271] For example, at least one of the wireless communication signals may include bandwidth information regarding the frequency bandwidth used for the wireless access node device. The estimated throughput may be determined based on the path information and the bandwidth information.

[0272] For example, when the above instructions are executed individually or collectively by the at least one processor, the electronic device may be caused to: identify, using the image data, material information and size information for at least one obstacle within a communication path for accessing the wireless access node device at the candidate spot, based on the location of the candidate spot defined for the wireless access node device and the electronic device; determine the estimated throughput when accessing the wireless access node device at the candidate spot according to the material information and the size information; identify the candidate spot as at least one recommended spot among the candidate spots based on the estimated throughput within a first range; and identify the candidate spot as at least one remaining candidate spot among the candidate spots based on the estimated throughput within a second range smaller than the first range.

[0273] For example, when the above instructions are executed individually or collectively by the at least one processor, the electronic device may be caused to identify the distance between each of the wireless access node device and the at least one obstacle using the image data, based on the location of the candidate spot. The estimated throughput may decrease as the distance decreases.

[0274] For example, when the above instructions are executed individually or collectively by the at least one processor, the electronic device may be caused to: identify, using the image data, interference information regarding whether at least one external electronic device exists around the candidate spot based on the location of the candidate spot defined for the wireless access node device and the electronic device; determine, according to the interference information, the estimated throughput when accessing the wireless access node device at the candidate spot; identify the candidate spot as the at least one recommended spot among the candidate spots based on the estimated throughput within a first range; and identify the candidate spot as the at least one remaining candidate spot among the candidate spots based on the estimated throughput within a second range smaller than the first range.

[0275] For example, the electronic device may further include at least one sensor (e.g., at least one sensor (170)). The wireless communication signals may include a first wireless communication signal, a second wireless communication signal, and a third wireless communication signal received sequentially from the wireless access node device. When the instructions are executed individually or collectively by the at least one processor: based on the reception of the first wireless communication signal, a first distance corresponding to a first location of the electronic device identified through the at least one sensor and the RSSI (received signal strength indicator) of the first wireless communication signal; based on the reception of the second wireless communication signal, a second distance corresponding to a second location of the electronic device identified through the at least one sensor and the RSSI of the second wireless communication signal; based on the reception of the third wireless communication signal, a third distance corresponding to a third location of the electronic device identified through the at least one sensor and the RSSI of the third wireless communication signal; Based on positioning of the wireless access node device using the first position, the second position, the third position, the first distance, the second distance, and the third distance, the position of the wireless access node device defined for the electronic device is determined; and the electronic device can be made to identify the position of each of the candidate spots defined for the wireless access node device and the electronic device using the image data and the determined position of the wireless access node device.

[0276] For example, when the above instructions are executed individually or collectively by the at least one processor: the electronic device may be caused to identify, based on the event, the wireless access node device for the event among the wireless access node devices around the electronic device, using identifier information for each of the identifiers of the wireless access node devices. The identifier information may be included in the wireless communication signals received from the wireless access node devices.

[0277] As described above, an electronic device (e.g., electronic device (101)) may include a camera (e.g., camera (130)); a communication circuit for Wi-Fi (wireless fidelity) (e.g., communication circuit (180)); at least one processor (e.g., at least one processor (110)) including a processing circuit; and a memory (e.g., memory (120)) that stores instructions and includes one or more storage media. When the instructions are executed individually or collectively by the at least one processor, they include: identifying an event for Wi-Fi use; acquiring image data through the camera based on the event; using the image data to identify candidate spots for Wi-Fi use within a location associated with the event; receiving wireless communication signals from a wireless access node device around the electronic device; and using the wireless communication signals and the image data to identify the location of each of the candidate spots defined for the wireless access node device and the electronic device. The electronic device may be configured to determine estimated throughputs when accessing the wireless access node device at each of the candidate spots based on the location of each of the candidate spots; identify at least one recommended spot among the candidate spots based on at least a portion of the estimated throughputs; and provide information about the at least one recommended spot to guide access to the wireless access node device at the at least one recommended spot.

[0278] For example, when the above instructions are executed individually or collectively by the at least one processor, the electronic device may be caused to: determine the distance between the candidate spot and the wireless access node device based on the location of the candidate spot defined for the wireless access node device and the electronic device; determine the estimated throughput when accessing the wireless access node device from the candidate spot according to the distance, wherein the estimated throughput decreases as the distance increases; identify the candidate spot as the at least one recommended spot among the candidate spots based on the estimated throughput within a first range; and identify the candidate spot as the at least one remaining candidate spot among the candidate spots based on the estimated throughput within a second range smaller than the first range.

[0279] For example, when the above instructions are executed individually or collectively by the at least one processor, the electronic device may be caused to: identify, using the image data, path information regarding whether a communication path for accessing the wireless access node device from the candidate spot corresponds to a line of sight (LOS) or a non-line of sight (NLOS), based on the location of the candidate spot defined for the wireless access node device and the electronic device; determine, according to the path information, the estimated throughput when accessing the wireless access node device from the candidate spot, and the throughput estimated according to the path information corresponding to the LOS is greater than the throughput estimated according to the path information corresponding to the NLOS; identify the candidate spot as the at least one recommended spot among the candidate spots based on the estimated throughput within a first range; and identify the candidate spot as the at least one remaining candidate spot among the candidate spots based on the estimated throughput within a second range smaller than the first range.

[0280] For example, at least one of the wireless communication signals may include bandwidth information regarding the frequency bandwidth used for the wireless access node device. The estimated throughput may be determined based on the path information and the bandwidth information.

[0281] For example, when the above instructions are executed individually or collectively by the at least one processor, the electronic device may be caused to: identify, using the image data, material information and size information for at least one obstacle within a communication path for accessing the wireless access node device at the candidate spot, based on the location of the candidate spot defined for the wireless access node device and the electronic device; determine the estimated throughput when accessing the wireless access node device at the candidate spot according to the material information and the size information; identify the candidate spot as at least one recommended spot among the candidate spots based on the estimated throughput within a first range; and identify the candidate spot as at least one remaining candidate spot among the candidate spots based on the estimated throughput within a second range smaller than the first range.

[0282] For example, when the above instructions are executed individually or collectively by the at least one processor, the electronic device may be caused to identify the distance between each of the wireless access node device and the at least one obstacle using the image data, based on the location of the candidate spot. The estimated throughput may decrease as the distance decreases.

[0283] For example, when the above instructions are executed individually or collectively by the at least one processor, the electronic device may be caused to: identify, using the image data, interference information regarding whether at least one external electronic device exists around the candidate spot based on the location of the candidate spot defined for the wireless access node device and the electronic device; determine, according to the interference information, the estimated throughput when accessing the wireless access node device at the candidate spot; identify the candidate spot as the at least one recommended spot among the candidate spots based on the estimated throughput within a first range; and identify the candidate spot as the at least one remaining candidate spot among the candidate spots based on the estimated throughput within a second range smaller than the first range.

[0284] For example, the electronic device may further include at least one sensor (e.g., at least one sensor (170)). The wireless communication signals may include a first wireless communication signal, a second wireless communication signal, and a third wireless communication signal received sequentially from the wireless access node device. When the instructions are executed individually or collectively by the at least one processor: based on the reception of the first wireless communication signal, a first distance corresponding to a first location of the electronic device identified through the at least one sensor and the RSSI (received signal strength indicator) of the first wireless communication signal; based on the reception of the second wireless communication signal, a second distance corresponding to a second location of the electronic device identified through the at least one sensor and the RSSI of the second wireless communication signal; based on the reception of the third wireless communication signal, a third distance corresponding to a third location of the electronic device identified through the at least one sensor and the RSSI of the third wireless communication signal; Based on positioning of the wireless access node device using the first position, the second position, the third position, the first distance, the second distance, and the third distance, the position of the wireless access node device defined for the electronic device is determined; and the electronic device can be made to identify the position of each of the candidate spots defined for the wireless access node device and the electronic device using the image data and the determined position of the wireless access node device.

[0285] For example, when the above instructions are executed individually or collectively by the at least one processor: the electronic device may be caused to identify, based on the event, the wireless access node device for the event among the wireless access node devices around the electronic device, using identifier information for each of the identifiers of the wireless access node devices. The identifier information may be included in the wireless communication signals received from the wireless access node devices.

[0286] For example, the electronic device may form a glasses-type wearable device or a head-mounted wearable device.

[0287] A non-transient computer-readable storage medium as described above may store one or more programs. When the one or more programs are executed by an electronic device (e.g., electronic device (101)) having a camera (e.g., camera (130)); a display (e.g., at least one display (140)); and a communication circuit for Wi-Fi (wireless fidelity) (e.g., communication circuit (180)), the program identifies an event for Wi-Fi use; based on the event, image data for an image to be displayed through the display is obtained through the camera; the image is displayed through the display; using the image data, candidate spots for Wi-Fi use within a location associated with the event are identified; wireless communication signals are received from a wireless access node device around the electronic device; and using the wireless communication signals and the image data, the location of each of the candidate spots defined for the wireless access node device and the electronic device is identified; The electronic device may include instructions for identifying at least one recommended spot among the candidate spots based on the location of each of the candidate spots; and for displaying the at least one recommended spot within the image displayed through the display, with the recommendation spot visually highlighted relative to at least one remaining candidate spot among the candidate spots, in order to guide access to the wireless access node device at the at least one recommended spot.

[0288] For example, the above one or more programs may include instructions that cause the electronic device to: determine the distance between the candidate spot and the wireless access node device based on the location of the candidate spot defined for the wireless access node device and the electronic device; determine the estimated throughput when accessing the wireless access node device from the candidate spot according to the distance, wherein the estimated throughput decreases as the distance increases; identify the candidate spot as at least one recommended spot among the candidate spots based on the estimated throughput within a first range; and identify the candidate spot as at least one remaining candidate spot among the candidate spots based on the estimated throughput within a second range smaller than the first range.

[0289] A non-transient computer-readable storage medium as described above may store one or more programs. When the one or more programs are executed by an electronic device (e.g., electronic device (101)) having a camera (e.g., camera (130)) and a communication circuit for Wi-Fi (wireless fidelity) (e.g., communication circuit (180)), the programs identify an event for Wi-Fi use; acquire image data through the camera based on the event; identify candidate spots for Wi-Fi use within a location associated with the event using the image data; receive wireless communication signals from a wireless access node device around the electronic device; identify the location of each of the candidate spots defined for the wireless access node device and the electronic device using the wireless communication signals and the image data; and identify at least one recommended spot among the candidate spots based on the location of each of the candidate spots. and may include instructions that cause the electronic device to provide information about the at least one recommended spot in order to guide access to the wireless access node device at the at least one recommended spot.

[0290] As described above, an electronic device (e.g., electronic device (101)) may include a wireless communication circuit (e.g., communication circuit (180)); a camera (e.g., camera (130)); at least one processor (e.g., at least one processor (110)) including a processing circuit; and a memory (e.g., memory (120)) that stores instructions and includes one or more storage media. When the instructions are executed individually or collectively by the at least one processor, the first information corresponding to a wireless access node device located within a wireless communication range with the electronic device via the wireless communication circuit; the second information corresponding to a candidate spot near the electronic device based at least partially on an image corresponding to the surroundings of the electronic device obtained through the camera; and the predicted communication quality for the wireless access node device at the candidate spot based at least partially on the first information and the second information. And, based at least in part on the predicted communication quality, the electronic device may be able to provide third information corresponding to a recommended spot for performing wireless communication through the wireless access node device.

[0291] For example, when the above instructions are executed individually or collectively by the at least one processor: the electronic device may be caused to obtain the relative position of the electronic device of the wireless access node device as at least part of the first information through the wireless communication circuit.

[0292] For example, when the above instructions are executed individually or collectively by the at least one processor, the electronic device may be caused to perform the operation of acquiring the relative position based at least partially on: first data corresponding to a first wireless communication signal received from the wireless access node device when the electronic device is located at a first position, second data corresponding to a second wireless communication signal received from the wireless access node device when the electronic device is located at a second position different from the first position, and third data corresponding to a third wireless communication signal received from the wireless access node device when the electronic device is located at a third position different from the first position and the second position.

[0293] For example, the electronic device may further include a sensor (e.g., at least one sensor (170)) for tracking the movement of a user of the electronic device. When the instructions are executed individually or collectively by the at least one processor, the electronic device may be caused to perform the operation of acquiring the relative position based further on the fourth data corresponding to the movement.

[0294] For example, when the above instructions are executed individually or collectively by the at least one processor: the electronic device may be caused to determine the distance between the candidate spot and the electronic device as at least part of the second information based on at least part of the image.

[0295] For example, when the above instructions are executed individually or collectively by the at least one processor, the electronic device may be caused to perform the operation of obtaining an angle between the wireless access node device and the candidate spot with respect to the electronic device; and estimating the predicted communication quality based at least partially on the relative position, the distance, and the angle.

[0296] For example, the electronic device may further include a microphone (e.g., microphone (150)). The instructions, when executed individually or collectively by the at least one processor, may cause the electronic device to receive voice input from a user of the electronic device through the microphone; and, if the text corresponding to the voice input does not contain a word related to wireless communication, to identify at least a portion of the voice input as a request for the third information based at least some of the context information related to the voice input.

[0297] For example, when the above instructions are executed individually or collectively by the at least one processor: the electronic device may be caused to use at least one of the following as at least part of the context information for the confirmation of the request: information corresponding to the location where the electronic device is located, usage history information for a specified application at the location, and activity information related to the location obtained based on the image.

[0298] For example, the wireless access node device may include a first wireless access node device; and a second wireless access node device. When the instructions are executed individually or collectively by the at least one processor, they may cause the electronic device to: select one of the first wireless access node device and the second wireless access node device as a target wireless access node device; and perform the operation of estimating the predicted communication quality with respect to the target wireless access node device.

[0299] For example, the first wireless access node device may correspond to a first SSID (service set identifier). The second wireless access node device may correspond to a second SSID. When the instructions are executed individually or collectively by the at least one processor, the electronic device may be caused to select the first wireless access node device as the target wireless access node device based at least in part on identifying that the first SSID contains text corresponding to the location where the electronic device is located, and the second SSID does not contain said text.

[0300] For example, when the above instructions are executed individually or collectively by the at least one processor: determining whether the wireless access node device is in a non-line of sight environment with respect to the candidate spot based on information corresponding to an object between the wireless access node device and the candidate spot identified from the image; and if it is determined that the wireless access node device is in the non-line of sight environment with respect to the candidate spot, causing the electronic device to lower the predicted communication quality.

[0301] For example, the candidate spot may include a first candidate spot having a first predicted communication quality and a second candidate spot having a second predicted communication quality lower than the first predicted communication quality. When the instructions are executed individually or collectively by the at least one processor, the electronic device may be caused to select the first candidate spot as the recommended spot.

[0302] For example, when the above instructions are executed individually or collectively by the at least one processor, the electronic device may be caused to select the second candidate spot instead of the first candidate spot as the recommended spot, based more on context information related to the user input of the electronic device.

[0303] For example, when the above instructions are executed individually or collectively by the at least one processor: the electronic device may be caused to identify at least one of the user’s preference for the surrounding environment of the spot analyzed from the image, the user’s expected activity, or device information corresponding to another electronic device being used by the user, as at least part of the context information.

[0304] For example, the electronic device may form a glasses-type wearable device or a head-mounted wearable device.

[0305] For example, when the above instructions are executed individually or collectively by the at least one processor: generating text describing the recommendation spot as at least part of the third information; and causing the electronic device to output the text converted into voice through a speaker included within the electronic device or an external speaker functionally connected to the electronic device.

[0306] For example, the electronic device may further include a display (e.g., at least one display (140)). The instructions, when executed individually or collectively by the at least one processor, may cause the electronic device to: display a preview image acquired using the camera as the image through the display; and, as at least part of the third information, display information regarding the recommended spot together with the preview image in association with an image area corresponding to the recommended spot in the preview image.

[0307] For example, the candidate spot may include a first candidate spot and a second candidate spot. When the instructions are executed individually or collectively by the at least one processor, the electronic device may: display a first indication representing a first image region corresponding to the first candidate spot in the preview image and a second indication representing a second image region corresponding to the second candidate spot so as to overlap at least partially with the preview image; and display information regarding the recommendation spot such that one indication corresponding to the recommendation spot among the first indication and the second indication is visually emphasized more than the other indication among the first image region and the second image region.

[0308] For example, when the above instructions are executed individually or collectively by the at least one processor, the electronic device may be caused to recognize at least one of an access point of a Wi-Fi (wireless fidelity) network and a base station of a cellular network as the wireless communication access node device.

[0309] A non-transient computer-readable storage medium as described above may store one or more programs. The one or more programs may include instructions that, when executed by an electronic device (e.g., electronic device (101)) having a wireless communication circuit (e.g., communication circuit (180)) and a camera (e.g., camera (130)): obtain first information corresponding to a wireless access node device located within a wireless communication range with the electronic device through the wireless communication circuit; obtain second information corresponding to a candidate spot near the electronic device based at least partially on an image corresponding to the surroundings of the electronic device obtained through the camera; estimate a predicted communication quality for the wireless access node device at the candidate spot based at least partially on the first information and the second information; and provide third information corresponding to a recommended spot for performing wireless communication through the wireless access node device based at least partially on the predicted communication quality.

[0310] The effects obtainable from the present disclosure are not limited to those mentioned above, and other unmentioned effects will be clearly understood by those skilled in the art to which the present disclosure belongs.

[0311] The electronic device according to the various embodiments disclosed in this document may be of various forms. The electronic device may include, for example, a portable communication device (e.g., a smartphone), a computer device, a portable multimedia device, a portable medical device, a camera, a wearable device, or a consumer electronics device. The electronic device according to the embodiments of this document is not limited to the devices described above.

[0312] The various embodiments of this document and the terms used therein are not intended to limit the technical features described in this document to specific embodiments, and should be understood to include various modifications, equivalents, or substitutions of said 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 said items unless the relevant context clearly indicates otherwise. In this document, phrases such as "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" may each include any one of the items listed together in the corresponding phrase, or all possible combinations thereof. Terms such as "first," "second," or "first" or "second" may be used simply to distinguish said components from other said components and do not limit said components in any other aspect (e.g., importance or order). Where any (e.g., 1st) component is referred to as "coupled" or "connected" to another (e.g., 2nd) component, with or without the terms "functionally" or "communicationly," it means that said any component may be connected to said other component directly (e.g., via a wire), wirelessly, or through a third component.

[0313] The term “module” as used in the 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, for example. A module may be a component formed integrally, or a minimum unit of said component or a part thereof 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).

[0314] Various embodiments of the present document may be implemented as software (e.g., program (1740)) comprising one or more instructions stored in a storage medium (e.g., internal memory (1736) or external memory (1738)) readable by a machine (e.g., electronic device (1701)). For example, a processor (e.g., processor (1720)) of the machine (e.g., electronic device (1701)) may call at least one of the one or more instructions stored from the storage medium and execute it. This enables the machine to be operated 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 that can be executed by an interpreter. The storage medium readable by the machine may be provided in the form of a non-transitory storage medium. Here, 'non-temporary' simply means that the storage medium is a tangible device and does not contain a signal (e.g., electromagnetic waves), and the term does not distinguish between cases where data is stored semi-permanently and cases where it is stored temporarily.

[0315] According to one embodiment, the method according to the various embodiments disclosed herein may be provided as included in a computer program product. The computer program product may be traded between a seller and a buyer as a product. The computer program product may be distributed in the form of a device-readable storage medium (e.g., compact disc read-only memory (CD-ROM)), or distributed online (e.g., download or upload) through an application store (e.g., Play Store™) or directly between two user devices (e.g., smartphones). In the case of online distribution, at least a portion of the computer program product may be temporarily stored or temporarily created on a device-readable storage medium, such as the memory of a manufacturer's server, an application store's server, or a relay server.

[0316] According to various embodiments, each component (e.g., module or program) of the components described above may include a singular or multiple entities, and some of the multiple entities may be separated and placed in other components. According to various embodiments, one or more of the components or operations of the aforementioned components may be omitted, or one or more other components or operations may be added. Generally or additionally, multiple components (e.g., module or program) may be integrated into a single component. In this case, the integrated component may perform one or more functions of each of the multiple components in the same or similar manner as those performed by the corresponding component among the multiple components prior to integration. According to various embodiments, operations performed by the module, program, or other components 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 an electronic device, camera; display; Communication circuit for Wi-Fi (wireless fidelity); At least one processor including a processing circuit; and Memory that stores instructions and includes one or more storage media, When the above instructions are executed individually or collectively by the at least one processor: Identify events for Wi-Fi usage; Based on the above event, image data for an image to be displayed through the above display is obtained through the camera; Displaying the above image through the above display; Using the above image data, identify candidate spots for Wi-Fi usage within the location associated with the above event; Receiving wireless communication signals from a wireless access node device around the electronic device; Using the above wireless communication signals and the above image data, the location of each of the above candidate spots defined for the above wireless access node device and the above electronic device is identified; Based on the location of each of the above candidate spots, identify at least one recommended spot among the above candidate spots; and To guide access to the wireless access node device at the above-mentioned at least one recommended spot, the above-mentioned at least one recommended spot is displayed within the image displayed through the display, while being visually highlighted relative to at least one remaining candidate spot among the candidate spots. The above electronic device, causing, Electronic device.

2. In Claim 1, When the above instructions are executed individually or collectively by the at least one processor: Based on the location of a candidate spot defined for the wireless access node device and the electronic device, the distance between the candidate spot and the wireless access node device is determined; When accessing the wireless access node device at the above candidate spot, the estimated throughput is determined according to the distance, and the estimated throughput decreases as the distance increases; Based on the estimated throughput within the first range, the candidate spot is identified as at least one recommended spot among the candidate spots; and Based on the estimated throughput within a second range smaller than the first range, the candidate spot is identified as at least one remaining candidate spot among the candidate spots. The above electronic device, causing, Electronic device.

3. In Claim 1, When the above instructions are executed individually or collectively by the at least one processor: Based on the location of a candidate spot defined for the wireless access node device and the electronic device, path information regarding whether a communication path for accessing the wireless access node device from the candidate spot corresponds to a line of sight (LOS) or a non-line of sight (NLOS) is identified using the image data; The estimated throughput when accessing the wireless access node device at the above candidate spot is determined according to the path information, and the throughput estimated according to the path information corresponding to LOS is greater than the throughput estimated according to the path information corresponding to NLOS; Based on the estimated throughput within the first range, the candidate spot is identified as at least one recommended spot among the candidate spots; and Based on the estimated throughput within a second range smaller than the first range, the candidate spot is identified as at least one remaining candidate spot among the candidate spots. The above electronic device, causing, Electronic device.

4. In Claim 3, At least one of the above wireless communication signals includes bandwidth information regarding the frequency bandwidth used for the wireless access node device, and The above estimated throughput is determined based on the path information and the bandwidth information, Electronic device.

5. In Claim 1, When the above instructions are executed individually or collectively by the at least one processor: Based on the location of a candidate spot defined for the wireless access node device and the electronic device, material information and size information for at least one obstacle within a communication path for accessing the wireless access node device from the candidate spot are identified using the image data; The estimated throughput when accessing the wireless access node device at the above candidate spot is determined according to the material information and the size information; Based on the estimated throughput within the first range, the candidate spot is identified as at least one recommended spot among the candidate spots; and Based on the estimated throughput within a second range smaller than the first range, the candidate spot is identified as at least one remaining candidate spot among the candidate spots. The above electronic device, causing, Electronic device.

6. In Claim 5, When the above instructions are executed individually or collectively by the at least one processor: Based on the location of the above candidate spot, the distance between each of the wireless access node device and the at least one obstacle is identified using the image data. The above electronic device, causing, The above estimated throughput decreases as the distance decreases, Electronic device.

7. In Claim 1, When the above instructions are executed individually or collectively by the at least one processor: Based on the location of a candidate spot defined for the wireless access node device and the electronic device, interference information regarding whether at least one external electronic device exists around the candidate spot is identified using the image data; Determining the estimated throughput when accessing the wireless access node device at the above candidate spot according to the interference information; Based on the estimated throughput within the first range, the candidate spot is identified as at least one recommended spot among the candidate spots; and Based on the estimated throughput within a second range smaller than the first range, the candidate spot is identified as at least one remaining candidate spot among the candidate spots. The above electronic device, causing, Electronic device.

8. In Claim 1, The above electronic device is, It includes at least one additional sensor, The above wireless communication signals include a first wireless communication signal, a second wireless communication signal, and a third wireless communication signal received sequentially from the wireless access node device, and When the above instructions are executed individually or collectively by the at least one processor: Based on the reception of the first wireless communication signal, a first distance corresponding to the first location of the electronic device identified through the at least one sensor and the RSSI (received signal strength indicator) of the first wireless communication signal is determined; Based on the reception of the second wireless communication signal, a second location of the electronic device identified through the at least one sensor and a second distance corresponding to the RSSI of the second wireless communication signal are determined; Based on the reception of the third wireless communication signal, a third location of the electronic device identified through the at least one sensor and a third distance corresponding to the RSSI of the third wireless communication signal are determined; Determining the position of the wireless access node device defined for the electronic device based on positioning for the wireless access node device using the first position, the second position, the third position, the first distance, the second distance, and the third distance; and Using the above image data and the above determined location of the above wireless access node device, to identify the location of each of the above candidate spots defined for the above wireless access node device and the above electronic device, The above electronic device, causing, Electronic device.

9. In Claim 1, When the above instructions are executed individually or collectively by the at least one processor: Based on the above event, the wireless access node device for the event among the wireless access node devices around the electronic device is identified using identifier information for each of the identifiers of the wireless access node devices. The above electronic device, causing, The above identifier information is included in the wireless communication signals received from the wireless access node devices, Electronic device.

10. In an electronic device, camera; Communication circuit for Wi-Fi (wireless fidelity); At least one processor including a processing circuit; and Memory that stores instructions and includes one or more storage media, When the above instructions are executed individually or collectively by the at least one processor: Identify events for Wi-Fi usage; Based on the above event, image data is acquired through the camera; Using the above image data, identify candidate spots for Wi-Fi usage within the location associated with the above event; Receiving wireless communication signals from a wireless access node device around the electronic device; Using the above wireless communication signals and the above image data, the location of each of the above candidate spots defined for the above wireless access node device and the above electronic device is identified; Based on the location of each of the above candidate spots, determine the estimated throughputs when accessing the wireless access node device at each of the above candidate spots; Based on at least some of the estimated throughputs above, identify at least one recommended spot among the candidate spots; and To guide access to the wireless access node device at the at least one recommended spot, to provide information about the at least one recommended spot, The above electronic device, causing, Electronic device.

11. In Claim 10, When the above instructions are executed individually or collectively by the at least one processor: Based on the location of a candidate spot defined for the wireless access node device and the electronic device, the distance between the candidate spot and the wireless access node device is determined; When accessing the wireless access node device at the above candidate spot, the estimated throughput is determined according to the distance, and the estimated throughput decreases as the distance increases; Based on the estimated throughput within the first range, the candidate spot is identified as at least one recommended spot among the candidate spots; and Based on the estimated throughput within a second range smaller than the first range, the candidate spot is identified as at least one remaining candidate spot among the candidate spots. The above electronic device, causing, Electronic device.

12. In Claim 10, When the above instructions are executed individually or collectively by the at least one processor: Based on the location of a candidate spot defined for the wireless access node device and the electronic device, path information regarding whether a communication path for accessing the wireless access node device from the candidate spot corresponds to a line of sight (LOS) or a non-line of sight (NLOS) is identified using the image data; The estimated throughput when accessing the wireless access node device at the above candidate spot is determined according to the path information, and the throughput estimated according to the path information corresponding to LOS is greater than the throughput estimated according to the path information corresponding to NLOS; Based on the estimated throughput within the first range, the candidate spot is identified as at least one recommended spot among the candidate spots; and Based on the estimated throughput within a second range smaller than the first range, the candidate spot is identified as at least one remaining candidate spot among the candidate spots. The above electronic device, causing, Electronic device.

13. In Claim 12, At least one of the above wireless communication signals includes bandwidth information regarding the frequency bandwidth used for the wireless access node device, and The above estimated throughput is determined based on the path information and the bandwidth information, Electronic device.

14. In Claim 10, When the above instructions are executed individually or collectively by the at least one processor: Based on the location of a candidate spot defined for the wireless access node device and the electronic device, material information and size information for at least one obstacle within a communication path for accessing the wireless access node device from the candidate spot are identified using the image data; The estimated throughput when accessing the wireless access node device at the above candidate spot is determined according to the material information and the size information; Based on the estimated throughput within the first range, the candidate spot is identified as at least one recommended spot among the candidate spots; and Based on the estimated throughput within a second range smaller than the first range, the candidate spot is identified as at least one remaining candidate spot among the candidate spots. The above electronic device, causing, Electronic device.

15. In Claim 14, When the above instructions are executed individually or collectively by the at least one processor: Based on the location of the above candidate spot, the distance between each of the wireless access node device and the at least one obstacle is identified using the image data. The above electronic device, causing, The above estimated throughput decreases as the distance decreases, Electronic device.

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