Electronic device and method for IoT device notification management thereof

Abstract

Provided are an electronic device and a method for IoT device notification management thereof. The electronic device comprises a display, a communication circuit, at least one processor, and a memory for storing instructions executable by the at least one processor. The instructions cause, when executed by the processor, the electronic device to receive notification data regarding states of external devices. The instructions cause the electronic device to collect the notification data through a first application that manages the external devices. The instructions cause the electronic device to group the collected notification data for each specific condition through the first application. The instructions cause the electronic device to, when the number of notification messages grouped through the first application exceeds a designated count within a designated time, generate a prompt text for requesting summarization of first notification data received during the designated time. The instructions cause the electronic device to transfer the prompt text generated through the first application to an artificial intelligence engine and receive a summary message on the basis of the first notification data. The instructions cause the electronic device to transfer the summary message to a second application that processes a notification output. The instructions cause the electronic device to output the summary message through the second application.

Description

Method for managing notifications of electronic devices and their IoT devices

[0001] The present disclosure relates to an electronic device and a method for managing notifications of the IoT device thereof.

[0002] Due to advancements in wireless communication technology, Internet of Things (IoT) functions, which enable information exchange between devices, are being supported in various service sectors. For instance, IoT functions can be applied to diverse fields such as smart homes, smart buildings, smart cities, smart cars (or connected cars), smart grids, healthcare, smart home appliances, or advanced medical services.

[0003] For example, in a smart home appliance system, an electronic device (e.g., a smartphone) can control and manage (monitor) IoT devices (e.g., smart home appliances) through application programs related to the Internet of Things. Additionally, each IoT device transmits notifications regarding its operating status or the occurrence of errors to the electronic device, and the electronic device can notify the notifications transmitted from each IoT device in real time (e.g., displaying notification messages on a notification bar).

[0004] When an electronic device receives notifications regarding operating status or error occurrences individually from each IoT device, it operates by simply notifying the user (e.g., a notification message) whenever a notification is received from each IoT device.

[0005] However, when there are many operating IoT devices, the excessive number of notification messages causes inconvenience for users who must manually delete or manage them one by one, and may lead to the problem of receiving duplicate unnecessary notifications. Furthermore, since notifications are sent in real-time regardless of their importance or priority, the user experience is degraded, and the notifications can cause stress.

[0006] Various embodiments propose an electronic device, method, and recording medium capable of summarizing and reorganizing notifications from IoT devices forming an electronic device and a group network (e.g., a home network), as well as notifying customized notifications based on user behavior patterns, electronic device status, and sensor information.

[0007] However, the problems intended to be solved in this disclosure are not limited to those mentioned above, and may be expanded in various ways without departing from the spirit and scope of this disclosure.

[0008] An electronic device according to one embodiment may include a display. An electronic device according to one embodiment may include a communication module including at least one communication circuit. An electronic device according to one embodiment may include at least one processor including processing circuitry. An electronic device according to one embodiment may include a memory that stores executable instructions by the at least one processor. According to one embodiment, the instructions, when executed by the processor, may cause the electronic device to receive notification data regarding the status of an external device from each external device through the communication circuit. According to one embodiment, the instructions, when executed by the processor, may cause the electronic device to collect the notification data received from each external device through a first application that manages external devices connected to the electronic device. According to one embodiment, the instructions, when executed by the processor, may cause the electronic device to group the collected notification data by specific conditions through the first application. According to one embodiment, the instructions may, when executed by the processor, cause the electronic device to generate a prompt text for requesting a summary of the first notification data received during the specified time when the number of notification messages grouped by the specific condition through the first application exceeds a specified number of times within the specified time. According to one embodiment, the instructions may, when executed by the processor, cause the electronic device to transmit the prompt text generated through the first application as an input value to an artificial intelligence engine to receive a summary message based on the first notification data from the artificial intelligence engine.According to one embodiment, the instructions may, when executed by the processor, cause the electronic device to transmit the summary message to a second application that processes a notification output related to the first application. According to one embodiment, the instructions may, when executed by the processor, cause the electronic device to output the summary message to the display through the second application.

[0009] A method for managing notifications of IoT devices of an electronic device according to one embodiment may include an operation of receiving notification data regarding the status of an external device from each external device through a communication circuit. A method according to one embodiment may include an operation of collecting notification data received from external devices through a first application that manages external devices connected to the electronic device. A method according to one embodiment may include an operation of grouping the collected notification data according to specific conditions through the first application. A method according to one embodiment may include an operation of generating a prompt text to request a summary of the first notification data received during the specified time when the number of notification messages grouped according to the specific conditions through the first application exceeds a specified number of times within a specified time. A method according to one embodiment may include an operation of receiving a summary message based on the first notification data from the artificial intelligence engine by transmitting the prompt text generated through the first application as an input value to the artificial intelligence engine. A method according to one embodiment may include an operation of transmitting the summary message to a second application that processes notification outputs related to the first application. A method according to one embodiment may include an operation of outputting the summary message to a display through the second application.

[0010] A non-transitory computer-readable medium storing instructions that cause the processor to perform operations when executed by a processor of an electronic device according to one embodiment may store instructions that cause the processor to perform an operation of receiving notification data regarding the status of external devices from each external device through a communication circuit. A recording medium according to one embodiment may store instructions that cause the operation of collecting notification data received from each external device to be performed through a first application that manages external devices connected to the electronic device. A recording medium according to one embodiment may store instructions that cause the operation of grouping the collected notification data according to specific conditions to be performed through the first application. A recording medium according to one embodiment may store instructions that cause the operation of generating prompt text to request a summary of the first notification data received during the specified time to be performed when the number of notification messages grouped according to the specific conditions through the first application exceeds a specified number of times within a specified time. A recording medium according to one embodiment may store a command that transmits a prompt text generated through the first application as an input value to an artificial intelligence engine, thereby performing an operation to receive a summary message based on first notification data from the artificial intelligence engine. A recording medium according to one embodiment may store a command that performs an operation to transmit the summary message to a second application that processes notification outputs related to the first application. A recording medium according to one embodiment may store a command that performs an operation to output the summary message to a display through the second application.

[0011] The electronic device, method, and recording medium according to various embodiments can reduce the number of notifications provided to a user and alleviate fatigue caused by unnecessary notifications by summarizing and integrating notifications transmitted from IoT devices forming a group network (e.g., a home network) with the electronic device according to specific criteria and outputting them as an integrated notification message. In addition, since individual notifications generated from each IoT device can be viewed as a single integrated notification, the user can easily identify important notification information.

[0012] The electronic device, method, and recording medium according to various embodiments can reduce unnecessary notifications to the user and deliver important notifications more effectively and improve the user experience by providing a differentiated processing method of notifications based on the user's habits and preferences regarding notification notifications.

[0013] The electronic device, method, and recording medium according to various embodiments can maximize user convenience by efficiently managing notifications transmitted from each IoT device and providing user-customized notifications according to the priority of the notifications.

[0014] The electronic device, method, and recording medium according to various embodiments provide notifications dynamically based on the user's perception of the situation, thereby allowing the user not to receive notifications at times when they are not needed, thus minimizing interference caused by notifications.

[0015] The electronic device, method, and recording medium according to various embodiments can simplify notification management by eliminating the need to separately process notifications for multiple IoT devices.

[0016] The effects obtainable from the present disclosure are not limited to those mentioned above, and other unmentioned effects may be provided, which are various effects that can be directly or indirectly understood by those skilled in the art to which the present disclosure pertains from the description below.

[0017] In relation to the description of the drawings, the same or similar reference numerals may be used for identical or similar components.

[0018] FIG. 1a is a block diagram of an electronic device in a network environment according to one embodiment.

[0019] FIG. 1b illustrates the configuration of a generative AI system according to one embodiment.

[0020] FIG. 2 illustrates an IoT (Internet of Things) network environment according to one embodiment.

[0021] FIG. 3 illustrates a diagram for schematically explaining operations for processing IoT notification events in an electronic device according to one embodiment.

[0022] FIG. 4 illustrates a notification management method for an IoT device of an electronic device according to one embodiment.

[0023] FIG. 5 illustrates examples of user interface screens displaying IoT notification messages according to one embodiment.

[0024] FIGS. 6a to 6e illustrate notification management methods for an IoT device of an electronic device according to one embodiment.

[0025] FIG. 7 illustrates a notification management method for an IoT device of an electronic device according to one embodiment.

[0026] FIG. 8 illustrates examples of user interface screens displaying IoT notification messages according to one embodiment.

[0027] FIGS. 9a to 9c illustrate examples of user interface screens displaying IoT notification messages in a flexible electronic device according to one embodiment.

[0028] Each of the embodiments described with reference to the drawings of the present disclosure may be configured independently as a single embodiment. Each of the embodiments described with reference to the drawings of the present disclosure may operate independently as a single embodiment. At least two of the embodiments described with reference to the drawings of the present disclosure may be configured by combining. At least two of the embodiments described with reference to the drawings of the present disclosure may operate by combining. For example, at least a part of the embodiment of FIG. 1 and at least a part of the embodiment of FIG. 2 may operate by combining with each other.

[0029] When at least two of the embodiments described with reference to the drawings of the present disclosure are combined, at least some of the configurations and / or at least some operations included in each embodiment may be omitted.

[0030] The electronic device 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.

[0031] FIG. 1a is a block diagram of an electronic device in a network environment according to one embodiment.

[0032] Referring to FIG. 1a, in a network environment (100), an electronic device (101) may communicate with an electronic device (102) through a first network (198) (e.g., a short-range wireless communication network) or with at least one of an electronic device (104) or a server (108) through a second network (199) (e.g., a long-range wireless communication network). According to one embodiment, the electronic device (101) may communicate with the electronic device (104) through a server (108). According to one embodiment, the electronic device (101) may include a processor (120), memory (130), input module (150), sound output module (155), display module (160) (or display), audio module (170), sensor module (176), interface (177), connection terminal (178), haptic module (179), camera module (180), power management module (188), battery (189), communication module (190), subscriber identification module (196), or antenna module (197). In some embodiments, at least one of these components (e.g., connection terminal (178)) may be omitted from the electronic device (101), or one or more other components may be added. In some embodiments, some of these components (e.g., sensor module (176), camera module (180), or antenna module (197)) may be integrated into a single component (e.g., display module (160)).

[0033] The processor (120) includes at least one processing circuitry, and the at least one processing circuitry can control at least one other component (e.g., a hardware or software component) of the electronic device (101) connected to the processor (120) by executing software (e.g., a program (140)), and can perform various data processing or operations. According to one embodiment, as at least part of the data processing or operations, the processor (120) can store commands or data received from other components (e.g., a sensor module (176) or a communication module (190)) in a volatile memory (132), process the commands or data stored in the volatile memory (132), and store the resulting data in a non-volatile memory (134). According to one embodiment, the processor (120) may include a main processor (121) (e.g., a central processing unit or an application processor) or an auxiliary processor (123) 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 (101) includes a main processor (121) and an auxiliary processor (123), the auxiliary processor (123) may be configured to use less power than the main processor (121) or to be specialized for a designated function. The auxiliary processor (123) may be implemented separately from the main processor (121) or as part thereof.

[0034] The auxiliary processor (123) may control at least some of the functions or states associated with at least one component of the electronic device (101) (e.g., display module (160), sensor module (176), or communication module (190)) on behalf of the main processor (121) while the main processor (121) is in an inactive (e.g., sleep) state, or together with the main processor (121) while the main processor (121) is in an active (e.g., application execution) state. According to one embodiment, the auxiliary processor (123) (e.g., image signal processor or communication processor) may be implemented as part of another functionally related component (e.g., camera module (180) or communication module (190)). According to one embodiment, the auxiliary processor (123) (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 (101) itself where the artificial intelligence is performed, or through a separate server (e.g., server (108)). 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.

[0035] Memory (130) can store various data used by at least one component of the electronic device (101) (e.g., processor (120) or sensor module (176)). The data may include, for example, software (e.g., program (140)) and input or output data for related instructions. Memory (130) may include volatile memory (132) or non-volatile memory (134). Memory (130) can store instructions executable by the processor (120) or the electronic device (101).

[0036] The program (140) may be stored as software in memory (130) and may include, for example, an operating system (142), middleware (144), or an application (146).

[0037] The input module (150) can receive commands or data to be used for a component of the electronic device (101) (e.g., processor (120)) from outside the electronic device (101) (e.g., user). The input module (150) 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).

[0038] The sound output module (155) can output a sound signal to the outside of the electronic device (101). The sound output module (155) 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.

[0039] A display module (160) (or a display) can visually provide information to an external (e.g., user) of the electronic device (101). The display module (160) 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 (160) 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.

[0040] The audio module (170) can convert sound into an electrical signal or, conversely, convert an electrical signal into sound. According to one embodiment, the audio module (170) can acquire sound through the input module (150) or output sound through the sound output module (155) or an external electronic device (e.g., electronic device (102)) (e.g., speaker or headphones) connected directly or wirelessly to the electronic device (101).

[0041] The sensor module (176) may include at least one sensor. The sensor module (176) may detect the operating state of the electronic device (101) (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 (176) 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.

[0042] The interface (177) may support one or more specified protocols that can be used for the electronic device (101) to be connected directly or wirelessly to an external electronic device (e.g., electronic device (102)). According to one embodiment, the interface (177) may include, for example, a high definition multimedia interface (HDMI), a universal serial bus (USB) interface, an SD card interface, or an audio interface.

[0043] The connection terminal (178) may include a connector through which the electronic device (101) can be physically connected to an external electronic device (e.g., electronic device (102)). According to one embodiment, the connection terminal (178) may include, for example, an HDMI connector, a USB connector, an SD card connector, or an audio connector (e.g., a headphone connector).

[0044] The haptic module (179) can convert an electrical signal into a mechanical stimulus (e.g., vibration or movement) or an electrical stimulus that can be perceived by the user through tactile or kinesthetic senses. According to one embodiment, the haptic module (179) may include, for example, a motor, a piezoelectric element, or an electric stimulation device.

[0045] The camera module (180) includes at least one camera and can capture still images and video. According to one embodiment, the camera module (180) may include one or more lenses, image sensors, image signal processors, or flashes.

[0046] The power management module (188) can manage power supplied to the electronic device (101). According to one embodiment, the power management module (188) can be implemented, for example, as at least part of a power management integrated circuit (PMIC).

[0047] The battery (189) can supply power to at least one component of the electronic device (101). According to one embodiment, the battery (189) may include, for example, a non-rechargeable primary battery, a rechargeable secondary battery, or a fuel cell.

[0048] A communication module (190) may include at least one communication circuit and may support the establishment of a direct (e.g., wired) communication channel or a wireless communication channel between an electronic device (101) and an external electronic device (e.g., electronic device (102), electronic device (104), or server (108)), and the performance of communication through the established communication channel. The communication module (190) may include one or more communication processors that operate independently of a processor (120) (e.g., application processor) and support direct (e.g., wired) communication or wireless communication. According to one embodiment, the communication module (190) may include a wireless communication module (192) (e.g., cellular communication module, short-range wireless communication module, or GNSS (global navigation satellite system) communication module) or a wired communication module (194) (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 (104) through a first network (198) (e.g., a short-range communication network such as Bluetooth, WiFi (wireless fidelity) direct, or IrDA (infrared data association)) or a second network (199) (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 (192) can identify or authenticate the electronic device (101) within a communication network such as the first network (198) or the second network (199) using subscriber information (e.g., International Mobile Subscriber Identifier (IMSI)) stored in the subscriber identification module (196).

[0049] The wireless communication module (192) can support 5G networks and next-generation communication technologies following 4G networks, for example, new radio access technology. NR access technology can 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 (192) can support a high-frequency band (e.g., mmWave band) to achieve a high data transmission rate, for example. The wireless communication module (192) 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 (192) can support various requirements specified in the electronic device (101), external electronic device (e.g., electronic device (104)), or network system (e.g., second network (199)). According to one embodiment, the wireless communication module (192) 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.

[0050] An antenna module (197) can transmit a signal or power to or from an external source (e.g., an external electronic device). According to one embodiment, the antenna module (197) 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 (197) 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 (198) or a second network (199), may be selected from the plurality of antennas, for example, by a communication module (190). A signal or power may be transmitted or received between the communication module (190) 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 (197).

[0051] According to one embodiment, the antenna module (197) 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.

[0052] At least some of the above components can 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 exchange signals (e.g., commands or data) with each other.

[0053] According to one embodiment, commands or data may be transmitted or received between an electronic device (101) and an external electronic device (104) through a server (108) connected to a second network (199). Each of the external electronic devices (102, or 104) may be the same or a different type of device as the electronic device (101). According to one embodiment, all or part of the operations performed on the electronic device (101) may be performed on one or more of the external electronic devices (102, 104, or 108). For example, if the electronic device (101) needs to perform a function or service automatically or in response to a request from a user or another device, the electronic device (101) 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 (101). The electronic device (101) 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 (101) may provide ultra-low latency services using, for example, distributed computing or mobile edge computing. In another embodiment, the external electronic device (104) may include an Internet of Things (IoT) device. The server (108) may be an intelligent server using machine learning and / or neural networks. According to one embodiment, the external electronic device (104) or the server (108) may be included within a second network (199).The electronic device (101) can be applied to intelligent services (e.g., smart home, smart city, smart car, or healthcare) based on 5G communication technology and IoT-related technology.

[0054] An electronic device (101) according to one embodiment may support artificial intelligence (AI) or generative artificial intelligence (GAI) functions. Generative AI functions may refer to a technology that generates new content based on content and can generate a new form of AI content (or generative content) by utilizing given input data or information. Here, AI content may refer to content that is entirely generated (or reconstructed / edited) or partially generated (or reconstructed / edited) based on generative AI (e.g., 3D objects, images, videos, audio, screen information, or text).

[0055] An electronic device (101) according to one embodiment may support generative AI functions in conjunction with a server (108). At least one of the electronic device (101) or the server (108) according to one embodiment may include the configuration of the generative AI system illustrated in FIG. 1b.

[0056] FIG. 1b illustrates the configuration of a generative AI system according to one embodiment.

[0057] Referring to FIG. 1b, the generative AI system may include a user interface (10100), an AI framework (10200), a generative AI model (10300), application and service components (10400), and a database component (10500).

[0058] A user interface (e.g., user query / response interface) (10100) according to one embodiment may receive a user query. The user query input may be in the form of natural language, images, and videos. The user interface (10100) may transmit not only data regarding the user query input but also context information to an AI framework (10200). The context information may include various additional information at the time of user input. Additionally, the user query input may be in a mixed form of the aforementioned natural language, images, sounds, and context information. Furthermore, the user query input may be in a non-natural language form that does not generate natural language, such as a menu selection (e.g., a creation request or a modification request). The user interface (10100) may output results of a generative artificial intelligence system to the user. The output may be in the form of natural language or specific content, and may also be provided in the form of actions requested by the user.

[0059] An AI framework (AI framework, 10200) according to one embodiment receives user query input and can coordinate and control each component necessary to perform the user's intent based on the user's query input. Such an AI framework (10200) may include a prompt design component (10210), an APIs / Plugins Management component (10230), and an output modification component (10250).

[0060] A user query or action entered in a user interface (10100) according to one embodiment may be transmitted to a prompt design component (10210). The prompt design component (10210) may be used to generate a prompt suitable for input into a large language model (LLM) or a large multimodal model (LMM). The prompt design component (10210) may be an AI component that uses machine learning algorithms or neural networks to develop better prompts over time. The prompt design component (10210) may generate a prompt by accessing a database component (10500) (e.g., a knowledge component) containing user preference data, a prompt library, and prompt examples, and transmit it to the large language model (LLM) or large multimodal model (LMM).

[0061] An API and plugin management component (10230) according to one embodiment can perform the role of communicating with external information when there is a request for additional information when transmitting user input as input to a generative model. The API and plugin management component (10230) establishes a channel to communicate with the outside of application and service components (10400) (e.g., AI Interface) through an API (application programming interface), thereby enabling access to various data sources. Additionally, the API and plugin management component (10230) can request an action through the API when the application or service needs to perform an action that ultimately executes a user query rather than an intermediate result. Information obtained from the outside can be transmitted as input to the generative model along with the user input.

[0062] An output modification component (10250) according to one embodiment can finely tune the output of a generative model. For example, the output modification component (10250) can verify whether the content generated through a language model (LLM) or a large-scale multimodal model (LMM) is irrelevant, contains biased content, or contains harmful content. Additionally, the output modification component (10250) can determine the extent to which the output matches the result desired by the user and, if additional processing is required, proceed with that process. Furthermore, the output modification component (10250) can configure and provide hints to the user to avoid unwanted output.

[0063] A generative AI model (10300) according to one embodiment generally refers to an artificial intelligence neural network that generates new forms of data based on user input information. Models that generate images may include, typically, a generative adversarial network (GAN) and a variational auto encoder (VAE). For example, a generative AI model may be a Diffusion-based generative model using a VAE and a Transformer structure. Additionally, a language-generating model may refer to a model trained to output the statistically most appropriate output value based on input values. Among the generative AI models (10300), a language-generating model may be, for example, models such as CHAT-GPT 3 and CHAT-GPT 4. As another example, a large multimodal model (LMM) may be a model capable of recognizing various forms of data input, such as text, images, and voice, and generating new data corresponding to them.

[0064] An electronic device (101) according to one embodiment may provide an AI function (or operation / service) by utilizing a part of the AI ​​system of FIG. 1b. For example, the electronic device (101) may support at least one of the following functions by utilizing the AI ​​function: a function to collect and group notification messages transmitted through a communication module from an external electronic device (e.g., IoT device); a function to group notification messages; a function to integrate and summarize (or reorganize) notifications satisfying specific conditions; a context awareness function; a function to learn user behavior patterns regarding notification messages; a function to adjust the notification frequency or priority of notification messages; and a function to dynamically control notification messages.

[0065] According to various embodiments, the electronic device (101) disclosed below may include at least some of the configurations described in FIG. 1a and FIG. 1b. In describing the electronic device (101) of the present disclosure, the same reference numerals are assigned to components substantially identical to the configurations disclosed in FIG. 1a and FIG. 1b above, and redundant descriptions of their functions may be omitted.

[0066] In the present disclosure, “notification event” may refer to the point in time when a system or electronic device recognizes that a notification state has occurred. “Notification data” may include specific values ​​or information / data describing the notification event together with the notification event. “Notification object / message” may refer to a structure / format form processed into a form deliverable to a user by combining the notification data with the notification event.

[0067] FIG. 2 illustrates an IoT (Internet of Things) network environment according to one embodiment. At least some of the components of FIG. 2 may be omitted, and the implementation may include additional components not illustrated.

[0068] Referring to FIG. 2, an IoT network environment according to one embodiment may include an IoT server (10) that supports IoT services, an electronic device (101) connected to the server (10), and external electronic devices (201, 202).

[0069] The IoT server (10) can communicate with the electronic device (101) and external electronic devices (201, 202) for data transmission and reception or remote control, for example, based on a network. The IoT server (10) can remotely control and / or monitor the external electronic devices (201, 202) based on a network, either through a relay device (e.g., AP, access point) or directly without a relay device.

[0070] The IoT server (10) can communicate with electronic devices or / and external electronic devices based on an edge computing system or a hub device network (e.g., Bluetooth, WiFi, WiFi direct, Z-wave, Zig-Bee, INSETEON, X10 or IrDA (infrared data association)).

[0071] The IoT server (10) may support direct communication with an electronic device (101) and / or an external electronic device (201, 202). Here, “direct communication” means communication without a relay device, for example, communication through a cellular communication network and / or a network.

[0072] The external electronic device (201, 202) is a sensor, home appliance, office electronic device, or device for performing a process that is placed (or located) within a local environment, such as a home, office, factory, building, external branch, or other types of site, for example, and there are no limitations on the type thereof. The external electronic device (201, 202) may be referred to as an IoT device.

[0073] The electronic device (101) can control and manage external electronic devices (201, 202) overall through an IoT application that supports IoT services. For example, the electronic device (101) may correspond to a portable electronic device (e.g., a smartphone). The electronic device (101) can transmit control commands to each external electronic device (201, 202). Here, the control command may refer to data that causes the external electronic device (201, 202) to perform a specific action. The specific action may include the output of information, sensing of information, reporting of information, and management of information (e.g., deletion or creation), and there is no limitation on the type thereof. The electronic device (101) may receive notifications from the external electronic devices (201, 202) regarding the results of performing the specific action or error reports.

[0074] According to one embodiment, the electronic device (101) may include an IoT application (210), an LLM AI engine (220), a notification manager (230), and a notification service (235). The electronic device (101) may further include components of the electronic device (101) illustrated in FIG. 1 (e.g., a processor (120), a memory (130), a communication module (190)).

[0075] Operations that can be implemented in the IoT application (210), LLM AI engine (220), notification manager (230), and notification service (235) can be stored as instructions in memory (130). When the instructions are executed by the processor (120), they can cause the electronic device (101) to perform a given operation through the IoT application (210), LLM AI engine (220), notification manager (230), and notification service (235).

[0076] The IoT application (210) may include a data collector (211), a prompt manager (212), a data module (213), and an AI agent (214).

[0077] A data collector (211) can collect notification data (hereinafter used interchangeably with the term “notification”) related to notification events transmitted from each external electronic device (e.g., IoT device) via a communication module (190) and store it in a data module (213). For example, notification events received from each external electronic device are not transmitted to a notification manager (230) but can be transmitted to a data collector (211) of an IoT application (210). The data collector (211) can transmit the notification data for the received notification events to an AI agent.

[0078] The data collector (211) can collect user behavior patterns (e.g., acknowledging the notification, ignoring the notification, removing the notification) regarding the notification message (or notification object) notified to the display and store them in the data module (213).

[0079] A prompt manager (212) can generate a prompt / prompt text requesting the creation of an integrated summary message of notifications (or notification data) and communicate with an LLM AI engine (220). The prompt manager (212) can, for example, generate a prompt / prompt text (input value) to be input to the LLM AI engine (220) using grouped notifications (or notification data). The prompt manager (212) can generate the prompt / prompt text by adding information about the notifications to be summarized to a prompt template. The prompt template may include instructions (or goals) indicating what the LLM AI engine (220) should perform using additional input values ​​(e.g., message information of the notifications to be summarized). The LLM AI engine (220) can analyze the data based on the instructions included in the prompt / prompt text to generate and output a response (e.g., a summary message).

[0080] The LLM AI engine (220) can generate an integrated summary message using prompt text input from the prompt manager (212). For example, the prompt text for summarizing five IoT notifications could be: "Washing is complete. 170Wh of energy was saved through AI saving mode. Wrinkle-free mode has started, and the laundry is ready to be removed at any time. A notification was also generated that the washing machine needs a cleaning cycle. Energy efficiency was maximized by optimizing the load of the washing machine. Summarize these notifications into a single message."

[0081] The LLM AI engine (220) can generate a response or result, for example, a summary message, "Washing complete. Save 170Wh in AI saving mode, start wrinkle-resistant mode, cleaning needed." using the aforementioned prompt / prompt text as input. The LLM AI engine (220) can send the result of the summary message to the prompt manager (212).

[0082] The AI ​​agent (214) can control and manage overall operations related to the IoT notification service using a data collector (211), a prompt manager (212), and a data module (213). The AI ​​agent (214) can perform at least one of the following operations: grouping of notifications (notification data), context awareness, learning user behavior patterns regarding notification messages and determining customized notifications, adjusting the frequency or priority of notification messages, and dynamic notification notification.

[0083] The AI ​​agent (214) can control dynamic notifications (e.g., real-time notification, delayed notification) for currently received notifications based on at least one of grouping notifications related to currently received IoT notifications, user behavior patterns regarding currently received notification types, and context awareness. Specific operations of the AI ​​agent (214) will be described in FIG. 3.

[0084] The notification manager (230) can process notifications (e.g., system notifications, application notifications, communication notifications) of the electronic device (101) to be output. When the notification manager (230) receives a notification request from each application or program, it can output / notify a notification object (e.g., a notification message) to the display based on the notification information received along with the request. The notification object (e.g., a notification message) can be output / notified to the display according to the order of the requests. For example, the notification manager (230) can output a notification object (e.g., a notification message) with an effect (e.g., sound output, silence, or vibration) to a notification notification area (e.g., a notification bar) according to the display method of the notification transmitted from the notification system (235).

[0085] According to one embodiment, the notification manager (230) may receive IoT notification requests related to external electronic devices from the IoT application (210) independently or in parallel with the notification request transmitted from the notification system (235). The notification manager (230) may display or notify a notification message (e.g., a single IoT notification message or an integrated summarized IoT notification message) in accordance with the IoT notification request received from the IoT application (210).

[0086] A notification system (235) (e.g., NotificationListenerService) can detect all notification events across the system in real time and perform advanced operations. The notification system (235) can define actions to be executed when a user selects a notification or clicks a button. For example, the notification system (235) (e.g., NotificationListenerService) can manage the scheduling of notifications and control the notification method and output. The notification system (235) can manage the priority of notifications and determine the notification method based on the importance of the notification event. For example, the notification system (235) can pass high-priority notifications to the notification manager (230) to output a notification object / message along with a notification effect (e.g., notification sound, vibration), and pass low-priority notifications to the notification manager (230) to output a notification object / message silently. The notification system (235) can pass notification requests to the notification manager (230) based on the notification method and display requirements determined by the notification scheduling. The notification manager (230) can display a notification object / message according to a notification request transmitted from the notification system (235) through a UI layer on a display or screen.

[0087] In the following embodiments, each operation may be performed sequentially, but is not necessarily performed sequentially. For example, the order of each operation may be changed, and at least two operations may be performed in parallel.

[0088] FIG. 3 illustrates a diagram for schematically explaining operations for processing IoT notifications in an electronic device according to one embodiment.

[0089] Referring to FIG. 3, an electronic device (101) according to one embodiment may include a software module for processing IoT notifications transmitted from an external electronic device (hereinafter referred to as an IoT device) through an IoT application (210) and providing customized notification messages to a user. When the IoT application (210) is executed, the processor (120) of the electronic device (101) can perform the operations of the software module illustrated in FIG. 3 by executing instructions stored in memory (130).

[0090] In operation 310, the IoT application (210) can detect a notification event generated from at least one IoT device through a communication module (190) under the control of the processor (120). The communication module (190) can transmit notification data, including the operating state or error state of the IoT device in relation to the notification event received from at least one IoT device, to the IoT application (210).

[0091] In operation 320, the IoT application (210) can collect notification data included in the notification received through the data collector (211) and store it in the data module (213).

[0092] For example, when a notification event is received from an IoT device, the communication module (190) may not transmit the detection of the notification event to the notification manager (230) but may notify the IoT application (210) that a notification from the IoT device has been detected. The data collector (211) may structure and index the currently received notification data. The data collector (211) may store the notification data related to the detected notification event in a structured form in the data module (213). The data collector (211) may transmit the notification data to the AI ​​agent (214).

[0093] In operation 330, the IoT application (210) can group and process notifications by device, time, event association, or recurring notification through the AI ​​agent (214).

[0094] The AI ​​agent (214) can group the notifications grouped in relation to the currently received notification event into one group, and send the data of the notifications grouped into one group to the prompt manager (212) to request prompt / prompt text for generating a summary message.

[0095] In operation 340, the IoT application (210) can generate a prompt / prompt text to generate a summary message based on the data of notifications included in the group through the prompt manager (212), and pass the prompt / prompt text as an input value to the AI ​​engine to generate the summary message.

[0096] In operation 350, the IoT application (210) can collect and learn user behavior patterns regarding notification messages through an AI agent (214) and store them in a data module (213). User behavior patterns may include at least one of checking notifications, ignoring notifications, or deleting notifications. Based on the results of learning user behavior patterns, the AI ​​agent (214) can provide customized notification displays for each notification type. The AI ​​agent (214) can customize the display method of notification messages visually or audibly according to the user's behavior patterns.

[0097] For example, if the "Wash Complete" notification from the washing machine is learned to be a notification frequently checked by the user, subsequent "Wash Complete" notifications from the washing machine may be pinned to the top of the notification bar and displayed with a highlighted color compared to other notification messages. On the other hand, if the "Robot Vacuum Cleaner Charge Complete" notification from the robot vacuum cleaner is learned to be a notification frequently ignored by the user, subsequent "Robot Vacuum Cleaner Charge Complete" notifications may be displayed in a simplified form without being pinned to the top.

[0098] In 360 operation, the IoT application (210) can determine whether to dynamically display notifications by adjusting the priority and frequency of notifications based on the currently recognized situation, and the AI ​​agent (214) recognizes the current situation based on at least one of the electronic device's state information and sensor information. Dynamic notifications may include at least one of a real-time method, a delayed method, or a summary method. For example, the AI ​​agent (214) can determine whether to adjust the IoT notification message to notify in real-time, notify after a delay, or provide it in an integrated summarized form depending on the currently recognized situation.

[0099] In operation 370, the IoT application (210) and the AI ​​agent (214) can display IoT notification messages. For example, the AI ​​agent (214) can notify the IoT notification message in real time or after a delay, depending on the currently recognized situation. Alternatively, the AI ​​agent (214) can provide the IoT notification message in an integrated summarized form.

[0100] FIG. 4 illustrates a notification management method for an IoT device of an electronic device according to one embodiment.

[0101] Referring to FIG. 4, in operation 410, the processor (120) of the electronic device (101) can detect the reception of an IoT notification event from an external electronic device (hereinafter referred to as an IoT device) through a communication module (190). Here, the external electronic device may be an IoT device connected to the electronic device (101) through an IoT application (210) or registered with the electronic device (e.g., washing machine, refrigerator, dryer, robot vacuum cleaner, air conditioner, induction cooker, air dresser, etc.). The communication module (190) can transmit the IoT notification event received from the IoT device to the IoT application.

[0102] For example, the electronic device (101) can receive notification events in real time from each IoT device in operation. The notification events may be events related to the operating status, control command result, or error status of an external electronic device, but the types of events are not limited.

[0103] For example, the electronic device (101) may receive five notification events from the refrigerator, such as “The door is open,” “Please close the door,” “The door is closed,” and “The device is ready for an update.” The electronic device (101) may receive two notification events from the washing machine, such as “Washing complete. 170Wh (23%) of energy saved in AI saving mode,” and “Starting wrinkle prevention mode. You may remove the laundry at any time.” Additionally, the electronic device (101) may receive the same notification three times repeatedly from the robot vacuum cleaner, such as “Please place the robot vacuum on a flat surface,” “Please place the robot vacuum on a flat surface,” and “Please place the robot vacuum on a flat surface,” if no change is made to the error state.

[0104] In operation 415, the processor (120) may collect and store notification data (hereinafter referred to as notification, IoT notification, and may be used interchangeably) related to a notification event received through an IoT application (210). The notification data related to the notification event may include the device type, the start of the notification, and the content of the notification.

[0105] In operation 420, the processor (120) can group the collected notification data (or IoT notifications) by specific conditions.

[0106] The processor (120) can analyze or classify collected notifications (e.g., IoT notifications) and perform grouping to group related notifications into one group according to various criteria. The processor (120) can determine the group to which each notification belongs based on the structured data (e.g., device_id, timestamp) of each received notification. For example, grouping criteria are described as grouping by device, grouping based on time, grouping based on event association, and grouping based on recurring notifications, but this is merely an example, and notifications may also be grouped according to other grouping criteria.

[0107] As the first group, device-based grouping classifies each notification based on the device_id and allows notifications to be grouped and managed by the IoT device from which the notification originated. For example, notifications transmitted from a washing machine (e.g., notifications structured as device_id ": "washer_001") can be managed as a single group called the washing machine group, and notifications transmitted from a robot vacuum cleaner (e.g., device_id ": ""robot_vacuum_003") can be managed as a robot vacuum cleaner group.

[0108] As a second group, time grouping can manage notifications that occur at adjacent times based on a time timestamp by grouping them into one group. If notifications occur within a specified time (e.g., 5 minutes), the processor (120) can manage notifications that occurred during the specified time by grouping them into one time group. At this time, the processor (120) can calculate the time difference between the timestamps stored in each notification. For example, if a laundry completion notification occurs at 14:30 and an AI saving mode activation notification occurs at 14:31, since the time difference is 1 minute, the laundry completion notification and the AI ​​saving mode activation notification can be managed by grouping them into one time group.

[0109] As a third group, event association-based grouping analyzes the event_type of notifications to manage association-based notifications by grouping them into a single group. For example, if a laundry completion notification and a notification indicating that AI energy saving mode is enabled coexist, the laundry completion notification and the notification indicating that AI energy saving mode is enabled can be managed by grouping them into a single association group. In association-based grouping, the event types to be grouped can be pre-specified, or event types not previously specified can be newly designated to be grouped into association groups based on AI-based learning results.

[0110] As a fourth group, recurring notification grouping allows recurring notifications to be grouped and managed when the same content occurs repeatedly over a preset period. For example, if the notification “Please place the robot vacuum on a flat surface” is received 5 times repeatedly from a robot vacuum cleaner over a preset period, the 5 received notifications can be grouped and managed as a single recurring notification group. The grouped notifications can be used to generate summary and summary messages for the notifications.

[0111] In operation 430, the processor (120) can perform data structuring and data indexing processing of collected notifications (e.g., IoT notifications). The processor (120) can store the collected notification data as structured information and perform indexing processing for information retrieval.

[0112] According to one embodiment, the processor (120) may store data related to a notification event (e.g., laundry completed. 170Wh (23%) energy saved in AI saving mode) in a data module as structured data (e.g., data in JSON format), such as the time of notification occurrence, the type of device (e.g., washing machine), and the content of the notification (e.g., laundry completed, AI saving mode (170Wh (23%))). The structured data may consist of various elements, and the elements described below are illustrated for illustrative purposes only and are not limited thereto.

[0113] For example, in JSON formatted data, `device_id` may contain the unique identifier (ID) of the device. For instance, a washing machine may be identified as "washer_001". `device_type` may contain the type of the device. For example, a washing machine may have the value `washing_machine`, a dryer may have `dryer`, and a robot vacuum cleaner may have `robot_vacuum`. `event_type` may contain the type of notification event that occurred. For example, "event_type: completion" indicates that the washing is complete and may have a value that distinguishes various events occurring on the device (e.g., error, completion, start). `event_description` may contain a specific description of the notification (e.g., the basic form of the message to be provided to the user, such as "Washing is complete"). `timestamp` may contain the time the notification occurred. `additional_info` is a section containing additional information and may be included optionally. For example, additional information such as activation information for AI saving mode or energy savings (170Wh) can be stored in this section. `priority` can represent the priority of a notification and can have values ​​such as "normal" or "high". Urgent and less urgent notifications can be distinguished based on the value expressed in `priority`. `status` can represent whether a notification has been read. For example, "status: unread" indicates that the user has not yet checked the notification message, while "status: read" indicates that the user has checked the notification message.

[0114] The electronic device (101) can collect and store IoT notifications as structured data, thereby allowing the notifications to be searched or filtered by specific device or specific notification type, and can also sort the notifications in chronological order. The electronic device (101) can be used to group notifications based on the structured data and to summarize and integrate the grouped notifications.

[0115] The electronic device (101) can index the structured data related to IoT notifications to facilitate searching (index structuring organization).

[0116] In operation 435, the processor (120) can store structured and indexed processed data (e.g., IoT notification data) in a data module.

[0117] In operation 440, the processor (120) can determine whether the requirements for summarizing and integrating grouped notifications are met in relation to the received notification data (e.g., IoT notifications).

[0118] According to one embodiment, the processor (120) may determine that the summarization and consolidation requirements are satisfied if the number of grouped notifications, including received notification events, exceeds a specified number within a specified time. For example, if five IoT notifications are received from a dryer within a specified time (e.g., five minutes), the processor (120) may determine that the summarization and consolidation requirements for the five notifications are satisfied.

[0119] In operation 445, if the processor (120) does not meet the summary and integration requirements with respect to the received notification (e.g., in operation 440, no), it may notify a single notification message (e.g., an IoT notification message containing only one notification data information) based on the received notification.

[0120] For example, the processor (120) may forward a notification request for a received notification event to the notification manager (212) if the summary and integration requirements regarding the received notification are not met, regardless of the grouping and integration processing of the notifications. The notification manager (212) may display a notification message based on the forwarded notification event (e.g., a single method notifying one message) on the display.

[0121] In operation 450, the processor (120) may generate a prompt text requesting the creation of a summary and integration notification if the requirements for the summary and integration of grouped notifications, including the received notification, are met (e.g., yes in operation 440). The processor (120) may pass the generated prompt text as an input to an AI engine (e.g., LMM AI engine).

[0122] For example, the processor (120) can receive a notification from the dryer that says “Drying is complete,” “Energy usage has been reduced by 30% through AI saving mode,” “Clothes are completely dry and ready to put in the next laundry,” and “Odor removal mode started automatically after drying”, and then receive a notification that says “Dryer filter needs cleaning.”

[0123] The processor (120) can generate prompt / prompt text such as “Drying is complete. Energy usage has been reduced by 30% via AI saving mode. The clothes are completely dry and ready to load the next load. Deodorizing mode started automatically after drying. Finally, a notification that the dryer filter needs cleaning has occurred. Integrate this notification and summarize it into a simple message.”

[0124] In operation 455, the processor (120) can receive a summary message from an AI engine (e.g., LLM AI engine (220)).

[0125] The processor (120) can receive a summary message generated by an input value from the AI ​​engine. For example, the processor can receive a summary message from the AI ​​engine such as "Drying complete. 30% energy saving in AI saving mode, odor removal mode started, filter cleaning needed."

[0126] Independently or in parallel, in 460 operation, the processor (120) can collect data on user behavior patterns of notification messages for IoT services.

[0127] According to one embodiment, the processor (120) can identify the behavior (or reaction) pattern of a user processing a notification message (e.g., a notification message displayed on a notification bar), and structure the user behavior pattern and the time at which the behavior occurred in the notification message and store them in a data module.

[0128] User behavior patterns regarding notification messages can be categorized into clicked, ignored, and dismissed. Clicked refers to the state where the user clicks or acknowledges the notification message. Ignored refers to the state where the notification disappears from the notification bar after a certain period of time without the user clicking on the message or taking any action. Dismissed refers to the state where the user removes or deletes the notification message without clicking or acknowledging it.

[0129] For example, if a user checks a notification message reporting the completion status of a washing machine, a data section for "user_action" can be added to a JSON-formatted data structure.

[0130] {

[0131] "device_id": "washer_001",

[0132] "device_type": "washing_machine",

[0133] "event_type": "completion",

[0134] "event_description": "Laundry is complete",

[0135] "timestamp": "2024-09-25T14:30:00Z",

[0136] "user_action": {

[0137] "action_type": "clicked",

[0138] "action_timestamp": "2024-09-25T14:31:00Z"

[0139] }

[0140] }

[0141] Here, “clicked” recorded in action_type indicates that the user clicked the notification to confirm it, and the data recorded in action_timestamp may indicate the time the user acknowledged the notification.

[0142] As another example, if the user ignores the notification message, the action_type is recorded as “ignored”, and the action_timestamp may record the time when the notification message was considered ignored (e.g., the time when the notification object disappeared from the notification bar without being acknowledged by another notification). As yet another example, if the user deletes the notification message without acknowledging it, the action_type is recorded as “dismissed”, and the action_timestamp may record the time when the notification message was deleted.

[0143] In operation 465, the processor (120) can analyze data on user behavior patterns of notification messages collected through the AI ​​agent.

[0144] According to one embodiment, the processor (120) can learn user behavior patterns collected over a certain period and determine the frequency and priority of notifications according to the type of notification for each pattern.

[0145] The processor (120) can analyze user behavior regarding ignoring or deleting the same type of notification message over a certain period (e.g., one week or one month). For example, if a notification saying "Please place on a flat surface" occurs multiple times from a robot vacuum cleaner and the user ignores it multiple times, the processor (210) can learn the robot vacuum cleaner notification type "Please place on a flat surface" as an ignored notification pattern. If the processor (120) analyzes that the rate at which a specific notification message is ignored or deleted exceeds a certain threshold (e.g., 50% or more), it can lower the importance of that notification type and reduce the notification frequency. The threshold for determining frequency may be adjusted according to the user's behavior pattern.

[0146] The processor (120) checks the types of notifications that the user repeatedly checks, and can increase the priority of the types of notifications that are frequently checked (e.g., washing machine completion notification).

[0147] Independently or in parallel, in 470 operation, the processor (120) can recognize the surrounding / current situation based on the state of the electronic device and sensor data.

[0148] According to one embodiment, the processor (120) can recognize the surrounding / current situation of the electronic device or user based on the state of the electronic device (e.g., do not disturb mode, battery status, screen status) and sensor data (e.g., accelerometer, position sensor, proximity sensor).

[0149] For example, the processor (120) can recognize whether the user is stationary or driving based on the movement and rotation state of the electronic device. The processor (120) can recognize whether the user is at home or in an office based on location information. The processor (120) can recognize whether the electronic device is in a pocket or a bag using proximity sensor data.

[0150] In operation 480, the processor (120) can determine a customized and dynamic notification display method based on an analysis of user behavior patterns and surrounding / current conditions.

[0151] For example, the AI ​​agent (214) can adjust the notification generation cycle so that if a notification is determined to be of low importance, the notification time interval is increased. For example, if the time interval of a notification determined to be of low importance is one hour, instead of generating a notification every hour, it can be adjusted so that a notification is generated once a day.

[0152] The processor (120) may adjust to provide a summary integrated notification on a daily or weekly basis rather than providing individual single notifications when a specific notification occurs frequently but is ignored by the user's behavioral pattern and is determined to be a notification type of low importance.

[0153] The processor (120) can adjust the priority of notification types so that they are fixed at the top of the notification list and are shown to the user first. For example, if a laundry completion notification is given increased priority based on user behavior pattern analysis, the AI ​​agent (214) can adjust the notification to be displayed at the top of the laundry completion notification rather than other notifications.

[0154] In operation 490, the processor (120) can determine whether the requirement to display a summary message is met.

[0155] For example, the processor (120) may determine to immediately output or notify the IoT notification message if the IoT notification message is determined to be displayed in a real-time manner in a single form. For another example, if the IoT notification message is scheduled to be notified after a delay, the processor (120) may determine the display requirements so that the IoT notification message is output when the scheduled time is satisfied or when the driving situation changes to a driving stop situation.

[0156] In operation 495, the processor (120) may output a summary message if the requirement to display an integrated notification message is met.

[0157] FIG. 5 illustrates examples of user interface screens displaying IoT notification messages according to one embodiment.

[0158] The notification UI (user interface) screen (510) illustrated in FIG. 5 may be a screen that extends the entire notification bar, notification window, or notification panel region placed at the top of the display, and the object representation of the illustrated summary message may also be applied to the UI of an application that supports IoT services.

[0159] Referring to FIG. 5, an electronic device (101) according to one embodiment is <501> As illustrated in the illustration, a summary message object (520, 530) generated based on notification requests grouped by specific criteria in relation to an IoT service can be displayed on the notification UI screen (510). The summary message objects (520, 530) can be displayed as a notification list in one area of ​​the notification UI screen (510).

[0160] Summary message objects (520, 530) may be displayed in a nested form, with the summary message object (520) displayed as the top layer and each notification object constituting the summary message displayed as a layer. For example, the summary message object (520 or 530) may include a group identification (e.g., IoT device identification information) (521), summary integration content (e.g., summary and integration content for notification content) (522), and extension items (525).

[0161] The electronic device (101) selects an extension item (525) based on user input. <502> As illustrated in the figure, each notification object (520-1, 520-2, 520-3) constituting the summary message can be displayed as an expanded list below the summary message object (520) displayed as the top layer.

[0162] The electronic device (101) <501> On the screen <502> When switching to the screen, the expanded item (525) can be converted to a collapsed item (526). The user <502> When a minimized item (526) is selected on the screen, the electronic device (101) <501> It can be switched back to the notification UI screen.

[0163] The electronic device (101) may display an integration indicator (523) for visually distinguishing between a single notification object and a summary integration notification on the summary message object (520, 530), but is not limited thereto. The electronic device (101) may process the notification objects using various graphic representation methods (e.g., color, frame) that can be visually distinguished in addition to the integration indicator.

[0164] FIGS. 6a to 6e illustrate notification management methods for an IoT device of an electronic device according to one embodiment.

[0165] As illustrated in FIG. 6a, specifically regarding the operation of collecting notifications and structuring data of an electronic device (101) according to one embodiment, the communication module (190) of the electronic device (101) can transmit notification generation and notification data (e.g., first notification) to a data collector (211) of an IoT application (210) based on receiving a notification event (e.g., first notification) related to an IoT service from an external electronic device (hereinafter, IoT device) in operation 6100.

[0166] In operation 6110, the data collector (211) can store notification data (e.g., the first notification) in the data module (213).

[0167] Notification data can be stored as structured data (e.g., a JSON-formatted data structure described in Fig. 4) including the time of notification occurrence, device type, and notification content.

[0168] In operation 6120, the data collector (211) can transmit notification data (e.g., first notification) transmitted from the IoT device to the AI ​​agent (214).

[0169] In operation 6130, the AI ​​agent (214) may request additional data (e.g., rules set for structuring, structuring method such as JSON, notification type, device information, previously stored notification data) from the data module (213) for structuring and indexing processing of a notification (e.g., first notification).

[0170] In operation 6140, the data module (213) can transmit additional data corresponding to the data request to the AI ​​agent (214).

[0171] In operation 6150, the AI ​​agent (214) can perform data cleaning and indexing processing on the received notification data (e.g., the first notification). For example, the AI ​​agent (214) can index the received notification by structuring it in a structured manner according to predetermined rules.

[0172] In operation 6160, the AI ​​agent (214) can store indexed notification data (e.g., first notification) in the data module (213).

[0173] The electronic device (101) can be efficiently utilized in managing, analyzing, searching, and filtering notifications by storing them as structured data according to a set rule for each received notification and sorting and managing them by device.

[0174] As illustrated in FIG. 6b, specifically regarding the grouping and notification summary integration operation of the electronic device (101), the communication module (190) of the electronic device (101) can collect notification data by transmitting it to a data collector (211) of the IoT application (210) based on receiving a notification event related to an IoT service from an external electronic device (hereinafter, IoT device) in operation 6200.

[0175] In operation 6210, the data collector (211) can store notification data in the data module (213). The data module (213) can store and collect notification events whenever a notification event is received.

[0176] In operation 6220, the data collector (211) can transmit the collected notification data to the AI ​​agent (214).

[0177] In operation 6230, the AI ​​agent (214) can group the collected notifications. For example, the AI ​​agent (214) can analyze or classify the collected notification events and perform grouping to group related notifications into one group according to various criteria. The criteria for grouping notifications are described as grouping by device, grouping based on time, grouping based on event relevance, and grouping of recurring notifications, but this is merely an example, and notifications may also be grouped according to other grouping criteria.

[0178] For example, the AI ​​agent (214) can perform device-based notification grouping in operation 6231, time-based grouping in operation 6232, event-related grouping in operation 6233, or recurring notification grouping in operation 6234.

[0179] In operation 6231, the AI ​​agent (214) can classify each notification event based on device_id and group notifications by IoT device from which the notification occurred. For example, notifications from a washing machine (e.g., notifications structured as device_id ": "washer_001") can be grouped and managed as a single group called the washing machine group, and notifications from a robot vacuum cleaner (e.g., device_id ": ""robot_vacuum_003") can be grouped and managed as the robot vacuum cleaner group.

[0180] In operation 6232, the AI ​​agent (214) can group notifications that occur at adjacent times based on a time timestamp into one group. At this time, the AI ​​agent (214) can calculate the time difference between the timestamps stored in each notification. For example, if a laundry completion notification occurs at 14:30 and an AI saving mode activation notification occurs at 14:31, since the time difference is 1 minute, the AI ​​agent (214) can group the laundry completion notification and the AI ​​saving mode activation notification into one time group.

[0181] In operation 6233, the AI ​​agent (214) can analyze the event_type of the notification and group notifications based on association into one group. For example, if a laundry completion notification and an AI saving mode activation notification coexist, the laundry completion notification and the AI ​​saving mode activation notification can be grouped into one association group.

[0182] In operation 6234, the AI ​​agent (214) can group repetitive notifications into one group if the same content occurs repeatedly for a preset period of time. For example, if the notification “Please place the robot vacuum on a flat surface” is received 5 times repeatedly from the robot vacuum for a preset period of time, the 5 received notifications can be grouped into one repetitive notification group.

[0183] In operation 6240, the AI ​​agent (214) can request the prompt manager (212) to generate a prompt for the summary integration of grouped notifications.

[0184] For example, the AI ​​agent (214) can generate a prompt text, such as “Drying is complete. Energy usage has been reduced by 30% through AI saving mode. The clothes are completely dry and ready to be put in the next laundry. Deodorizing mode started automatically after drying. Finally, a notification was received that the dryer filter needs cleaning. Integrate these notifications and summarize them into a simple message.” The prompt text can be set to include key information necessary to summarize the notifications, as well as the context and relevance of the notifications, to generate a summary message.

[0185] In operation 6250, the prompt manager (212) can transmit the generated prompt / prompt text to the LLM AI engine (220). The prompt / prompt text can be input as an input value to the LMM AI engine (220).

[0186] In operation 6260, the LLM AI engine (220) can pass the generated result (e.g., summary integration notification message) to the prompt manager (212) using the prompt / prompt text as input.

[0187] For example, a summary message for notifications classified as a dryer group can be generated as “Drying complete. Save 30% energy in AI save mode, start odor removal mode, filter cleaning required.”

[0188] In operation 6270, the prompt manager (212) can deliver a summary integration notification message to the AI ​​agent (214).

[0189] As illustrated in FIG. 6c, specifically regarding the operation of learning user behavior patterns of the electronic device (101) and providing customized notifications, in operation 6300, the notification manager (230) can display a notification message for an IoT service on the display (160). For example, when a first notification for “washing complete” is received from the washing machine, the electronic device (101) can display a notification message for “washing complete” on the display.

[0190] In operation 6310, the data collector (211) can collect user behavior pattern data by checking the user's behavior pattern (e.g., acknowledging, ignoring, or deleting) regarding a notification (e.g., the first notification) displayed on the display.

[0191] User behavior patterns can be categorized into clicked, ignored, and dismissed. Clicked refers to the state where the user clicks or acknowledges a notification message. Ignored refers to the state where the notification disappears from the notification bar after a certain period of time without the user clicking on the message or taking any action. Dismissed refers to the state where the user removes or deletes the notification message without clicking or acknowledging it.

[0192] In operation 6320, the data collector (211) can store user behavior data regarding a notification (e.g., a first notification) in the data module (213).

[0193] The data collector (211) can identify user behavior patterns for a notification and structure the user behavior patterns and the time at which the behavior occurred for the notification (e.g., the first notification) and store them in a data module.

[0194] For example, if the user checks the first notification displayed on the display, additional data such as "user_action"{"action_type": "clicked “"2024-09-25T14:31:00Z"} can be stored in the JSON format data structure of the first notification.

[0195] In operation 6330, the data module (213) can transmit data about user behavior patterns stored for data analysis to the AI ​​agent (214).

[0196] In operation 6340, the AI ​​agent (214) can analyze user behavior patterns based on data regarding the transmitted user behavior patterns.

[0197] The AI ​​agent (214) can perform learning on acknowledged notifications, learning on ignored notifications, and learning on deleted notifications. In the case of learning on acknowledged notifications, it identifies notification types that the user acknowledges above a certain threshold (e.g., laundry completion, AI saving mode notifications), and these notification types can be considered important notifications. In the case of learning on ignored notifications, it identifies notification types that the user ignores above an average threshold (e.g., robot vacuum cleaner charging status notifications), and these notification types can be considered low-importance notifications. In the case of learning on deleted notifications, it identifies notification types that the user deletes above an average threshold, and these notification types can be considered unnecessary notifications to the user.

[0198] In operation 6350, the AI ​​agent (214) can automatically adjust the notification frequency and priority based on the analysis results.

[0199] For example, the AI ​​agent (214) can learn user behavior patterns by notification type and reduce the frequency of ignored / deleted notification types and increase the priority of frequently checked notification types.

[0200] Regarding frequency control, in the 6351 operation, the AI ​​agent (214) can automatically control the frequency of occurrence of notification types that are ignored or deleted.

[0201] The AI ​​agent (214) can reduce the importance of notification types and decrease the frequency of notifications when the rate of being ignored or deleted is analyzed to be above a certain threshold (e.g., 50% or more). The threshold for determining frequency may be adjusted according to the user's behavioral patterns. For example, if the notification "Please place the robot vacuum cleaner on a flat surface" occurs 5 times, it can be adjusted to display it only once and consolidate it into a "5 occurrences" message.

[0202] In operation 6352, the AI ​​agent (214) can store data regarding the frequency-reduced notification type. For example, the AI ​​agent (214) can structure the frequency-reduced content and store it in a data module. For example, in a JSON-formatted data structure, data such as "user_action"{"action_count": 5" frequency_reduction": true "" can be additionally stored. Here, action_count means the number of times the same notification is repeated, and true in frequency_reduction means that the frequency of the notification has been automatically adjusted.

[0203] Regarding priority adjustment, in the 6353 operation, the AI ​​agent (214) can adjust the priority of notification types that are checked more frequently than a certain threshold by the user so that the priority is raised.

[0204] For example, the AI ​​agent (214) may increase the priority of notification types that are checked more frequently than a certain threshold (e.g., 70%) of the total notification ratio, considering them important notifications. The priority may be a value that is dynamically determined based on the user's behavioral patterns.

[0205] In operation 6354, the AI ​​agent (214) can store data for the notification type with increased priority.

[0206] For example, the AI ​​agent (214) can structure the content of the priority adjustment and store it in a data module. For example, in a JSON-formatted data structure, data such as "user_action"{" priority_increase": true " priority": "high"} can be additionally stored. Here, "high" in priority means that the notification has a high priority, and "true" in priority_increase means that the priority of the notification has increased.

[0207] In operation 6360, the AI ​​agent (214) can provide a customized notification to the user via the notification manager (230) based on frequency control and priority upgrading information. In operation 6370, the notification manager (230) can display the customized notification on the display.

[0208] The AI ​​agent (214) can adjust the notification generation cycle so that if a notification is determined to be of low importance, the notification time interval is increased. For example, if the time interval of a notification determined to be of low importance is one hour, instead of generating a notification every hour, it can be adjusted so that a notification is generated once a day.

[0209] The AI ​​agent (214) can be adjusted so that when a specific notification occurs frequently but is ignored by the user's behavioral pattern and is determined to be a notification type of low importance, it does not provide individual single notifications but instead provides summary integrated notifications on a daily or weekly basis.

[0210] The AI ​​agent (214) can adjust the priority of notification types so that they are fixed at the top of the notification list and are shown to the user first. For example, if a laundry completion notification is given increased priority based on user behavior pattern analysis, the AI ​​agent (214) can adjust the notification to be displayed at the top of the laundry completion notification rather than other notifications.

[0211] The AI ​​agent (214) can be made to highlight the notification type with increased priority using graphic objects such as colors or icons to distinguish it from other notifications, or to support vibration effects. For example, if the notification "Laundry is complete" has increased priority, the laundry complete notification can be provided with a red icon or vibration notification to inform the user that it is more important than other notifications.

[0212] The AI ​​agent (214) can display notification types with increased priority in real-time in the notification request. For example, notifications with increased priority can be displayed even in Do Not Disturb mode or during a meeting.

[0213] As illustrated in FIG. 6d, specifically regarding the situation awareness and dynamic notification control operation of the electronic device (101), in operation 6400, the AI ​​agent (214) can collect sensor data from the sensor module (176) (sensors) of the electronic device (101). The sensor data includes sensor data from various sensors such as an accelerometer, a gyroscope, and a GPS sensor, and the types of sensor data are merely examples and are not limited thereto.

[0214] In operation 6410, the AI ​​agent (214) may receive state information of the electronic device (101) from the processor (120) of the electronic device (101). The state information of the electronic device (101) may refer to information regarding the Do Not Disturb (DND) mode, battery status, or screen status, but the types of state information are examples only and are not limited thereto.

[0215] For example, Do Not Disturb mode can be activated when the user is in a meeting or resting at night.

[0216] In operation 6420, the AI ​​agent (214) can recognize the situation based on sensor data and the state information of the electronic device and dynamically process notifications according to the recognized current situation.

[0217] The AI ​​agent (214) can recognize whether the user is stationary or driving based on the movement and rotation state of the electronic device. The AI ​​agent (214) can recognize whether the user is at home or in an office based on location information. The AI ​​agent (214) can recognize whether the electronic device is in a pocket or a bag using proximity sensor data.

[0218] In relation to Do Not Disturb mode, in operation 6411, the AI ​​agent (214) can adjust to delay or summarize IoT notification messages when Do Not Disturb mode is enabled. For example, it can delay the notification of IoT notification messages until Do Not Disturb mode is disabled, or process IoT notification messages received while Do Not Disturb mode is enabled to summarize.

[0219] For example, if the AI ​​agent (214) detects that the user is in a meeting while in Do Not Disturb mode and the battery level is 15% or less, the washing completion notification from the washing machine may not be immediately notified, but may be processed to be notified after the meeting ends.

[0220] In relation to the low battery level situation, in operation 6412, the AI ​​agent (214) can limit the notification of low-importance IoT notification messages when the battery level is lower than a threshold. For example, when the battery is 20% or less, notifications of non-urgent or low-importance IoT notification messages can be processed so that they are not displayed.

[0221] In relation to the driving situation, in operation 6413, the AI ​​agent (214) may not notify the IoT notification message in real time, but may delay the IoT notification message until the driving ends or process it so that it is summarized.

[0222] For example, the AI ​​agent (214) may receive a notification event from the robot vacuum cleaner while the user behavior pattern is analyzed as ignoring the robot vacuum cleaner notification type. If the AI ​​agent (214) recognizes the situation in which the user is currently operating based on the movement and rotation state of the electronic device, it may delay the received notification from the robot vacuum cleaner and process it so that after operation ends, it can summarize the notifications delivered from the robot vacuum cleaner and provide a notification message.

[0223] In relation to normal situations (e.g., screen on, Do Not Disturb mode disabled), in the 6414 operation, the AI ​​agent (214) can process to notify IoT notification messages in real time when the electronic device is in a normal state and the screen is on.

[0224] In operation 6420, the notification manager (230) can deliver an IoT notification message (e.g., an IoT notification message for which notification processing is determined based on the situation) delivered from the AI ​​agent (214) to the display.

[0225] As illustrated in FIG. 6e, regarding the operation of displaying a notification message of an electronic device (101), in operation 6500, the AI ​​agent (214) may request the notification manager (230) to handle the notification processing determined according to the situation for the IoT notification message. The notification processing is exemplarily described as a real-time display method, a delayed display method, or a summary display method, but is merely an example and is not limited thereto.

[0226] Regarding real-time notifications, in the 6510 operation, the notification manager (230) can display or notify the IoT notification message determined by the real-time display method on the display in real time.

[0227] Regarding delayed notifications, in operation 6520, the notification manager (230) may schedule IoT notification messages determined by the delay display method with a delayed notification time. In operation 6525, the electronic device (e.g., processor (120)) may transmit status information to the notification manager (230) that has changed to a Do Not Disturb mode release, a driving release state, or a charging complete state. In operation 6527, the notification manager (230) may display or notify the delayed IoT notification message on the display based on confirmation of the status change.

[0228] Regarding summary notifications, in operation 6530, the notification manager (230) can group the IoT notification messages determined by the summary integration method and create a summary message as one. In operation 6535, the summary message can be displayed or notified on a display.

[0229] FIG. 7 illustrates a notification management method for an IoT device of an electronic device according to one embodiment.

[0230] In operation 710, the processor (120) of the electronic device (101) can detect the occurrence of an IoT notification. For example, the processor (120) can detect a notification event generated from at least one IoT device through a communication module (190). Based on the notification event received from at least one IoT device, the communication module (190) can transmit notification data transmitted along with the notification event (e.g., time of notification occurrence, type of device, operating status or error status of the IoT device) to an IoT application (210).

[0231] In operation 720, the processor (120) can collect user behavior data related to IoT notifications.

[0232] The processor (120) can identify the behavior (or reaction) pattern of a user processing a notification message (e.g., a notification message displayed in a notification bar). The user's behavior pattern regarding the notification message can be classified as clicked, ignored, or dismissed. Clicked may mean a state where the user clicks or acknowledges the notification message. Ignored may mean a state where the notification disappears from the notification bar without the user clicking on the notified notification message or taking any action for a certain period of time. Dismissed may mean a state where the user removes or deletes the notification message without clicking or acknowledging it.

[0233] In operation 730, the processor (120) can store user behavior data. The processor (120) can structure user behavior patterns and the time at which the behavior occurred and store them in a data module.

[0234] For example, when a user checks a notification message reporting the completion status of a washing machine, data sections such as "user_action: {"action_type": "clicked", "action_timestamp": "2024-09-25T14:31:00Z"} can be added and stored in a JSON data structure.

[0235] In operation 740, the processor (120) can analyze user behavior patterns in relation to IoT notifications.

[0236] For example, in the case of a washing machine “washing complete” notification, the processor (120) analyzes that the washing machine “washing complete” notification type has a behavioral pattern in which the user frequently checks it, whereas in the case of a robot vacuum “charge complete” notification, the processor (120) analyzes that the robot vacuum “charge complete” notification type has a behavioral pattern in which the user ignores it.

[0237] In operation 750, the processor (120) can adjust the frequency of notifications based on the results of learning the user's behavior pattern.

[0238] For example, the processor (120) may reduce the frequency of notifications for types of IoT notifications that the user ignores or deletes. Alternatively, the processor (120) may provide them in a single integrated form or increase the notification time interval if the types of notifications that the user ignores or deletes are duplicates.

[0239] In operation 760, the processor (120) can determine the notification priority.

[0240] For example, the processor (120) can adjust the priority of the notification types among the IoT notifications that the user checks, fixing them to the top of the notification bar or providing them with visual graphic effects that are highlighted compared to other notifications. Alternatively, the processor (120) can adjust the notifications so that for types analyzed as important notifications that the user checks frequently, the notification is output immediately in real time, and is output with visual / auditory effects even in Do Not Disturb mode.

[0241] In operation 770, the processor (120) can display customized notification messages with adjusted frequency and priority based on the results of IoT notification analysis.

[0242] FIG. 8 illustrates examples of user interface screens displaying IoT notification messages according to one embodiment.

[0243] Referring to FIG. 8, an electronic device (101) according to one embodiment can provide IoT notification messages in various display ways depending on the situation recognition result.

[0244] For example, in a first situation where the user is in a meeting and Do Not Disturb mode is activated, the electronic device (101) may receive a notification from the washing machine saying, “Washing is complete. 170 Wh of energy saved in AI saving mode,” a notification from the dryer saying, “Drying is complete,” and a notification from the robot vacuum cleaner saying, “Robot charging is complete.” The electronic device (101) recognizes the first situation, delays the display of each notification, and then receives a first IoT notification message (815) that summarizes and integrates the three notifications as “Washing complete, 170 Wh saved, Drying complete, Robot charging complete.” <801> It can be displayed on the first UI screen (810) shown in the illustration. The first UI screen (810) may be a lock screen or standby screen where a call object (811) and a camera object (813) are displayed, but this is merely an example and is not limited thereto. The first IoT notification message (815) may include an AI indicator (818) indicating that it is a message that integrates multiple notifications through AI. Through the AI ​​indicator, the user can recognize that the IoT notification is a summary notification integrated based on multiple notifications.

[0245] When the user selects the first IoT notification message (815), the electronic device (101) <802> As illustrated in the figure, IoT notification messages (830, 840) with delayed notification output may be displayed due to the electronic device (101) being locked or having its Do Not Disturb mode activated. The IoT notification messages (830, 840) may be summary-type IoT notification messages (830) in which notifications grouped by specific IoT device are integrated, but a single-type IoT notification message (840) may also be displayed. The integrated summary-type IoT notification messages (830) may include an AI indicator (831) and an extension object (835) that extends the display of the grouped notifications.

[0246] <803> The notification UI screen (820) illustrated in the image may be a screen that displays multiple IoT notification messages transmitted from multiple IoT devices. The electronic device (101) may display a summary type IoT notification message (830) in which multiple notifications are integrated according to grouping conditions, along with one single type IoT notification message (840) received from the washing machine.

[0247] FIGS. 9a to 9c illustrate examples of user interface screens displaying IoT notification messages in a flexible electronic device according to one embodiment.

[0248] Referring to FIGS. 9a through 9c, an electronic device (101) according to one embodiment may have a changeable structure capable of utilizing a large screen display. As part of the changeable structure, the electronic device (101) may have a foldable structure capable of varying the display area of ​​a flexible display through at least two housing structures rotatably coupled to each other. The electronic device illustrated in FIGS. 9a through 9c illustrates an example of a multi-foldable in which a first folding axis is implemented in an in-folding manner and a second folding axis is implemented in an out-folding manner, but is not limited thereto.

[0249] The electronic device (101) can provide the functions for notification integration, notification customization, and dynamic notification of the present disclosure to any electronic device in which the display area for displaying visual information of the display is variable. When the electronic device is in use in a first state (e.g., fully folded state), the display <901> As illustrated in the figure, the first area is activated, and the electronic device (101) can display the first UI screen (910) through the first area. While the electronic device (101) is in use in the first state, notifications may occur simultaneously from the washing machine, robot vacuum cleaner, and refrigerator. The electronic device (101) can display a summary message (920) (e.g., an IoT notification message) of the notifications generated from the washing machine, robot vacuum cleaner, and refrigerator based on generative AI. The integrated summary notification message can induce the user to check details through additional actions by providing IoT notification messages such as "Three notifications have occurred from smart home devices" or "Washing complete, robot charging complete, refrigerator door open." Although not illustrated in the figure, the integrated summary notification message may further include the AI ​​indicator and extension object illustrated in FIG. 8.

[0250] When the electronic device switches to a second state (e.g., partially folded, partially unfolded state), the display <902> As illustrated in the figure, the first area and the second area are activated, and the electronic device (101) can display a second UI screen (911) through the second area. The second UI screen may display notification messages (921, 923, 935) grouped by AI. According to some embodiments, when a summary message (920) displayed on the first UI screen is selected, the grouped notification messages (921, 923, 925) may be displayed on the second UI screen.

[0251] When the electronic device switches to a third state (e.g., fully unfolded state), the display <903> As illustrated in [Image], the first area, the second area, and the third area are activated, and the display can display the third UI screen (912) through the third area.

[0252] When an electronic device is in use in a third state and notifications are generated simultaneously from a washing machine, a robot vacuum cleaner, and a refrigerator, a summary message (920) (e.g., an IoT notification message) of the notifications generated from the washing machine, a robot vacuum cleaner, and a refrigerator based on generative AI may be displayed on the first UI screen (910), a list of notifications (921) generated from the washing machine may be displayed on the second UI screen (911), and a list of notifications (930) generated from the refrigerator and a robot vacuum cleaner may be displayed on the third UI screen (912). The display format of the IoT notification message illustrated in FIGS. 9a to 9c is merely an example, and the summary content of the messages, object forms, interaction input objects with the user, or the layout structure of each UI screen may be modified according to the user's behavioral patterns and recognized situations.

[0253] An electronic device according to one embodiment may include a display. An electronic device according to one embodiment may include a communication module including at least one communication circuit. An electronic device according to one embodiment may include at least one processor including a processing circuitry. An electronic device according to one embodiment may include a memory that stores executable instructions by the at least one processor. According to one embodiment, the instructions, when executed by the processor, may cause the electronic device to receive notification data regarding the status of external devices from each external device through the communication circuit. According to one embodiment, the instructions, when executed by the processor, may cause the electronic device to collect the notification data received from each external device through a first application that manages external devices connected to the electronic device. According to one embodiment, the instructions, when executed by the processor, may cause the electronic device to group the collected notification data by specific conditions through the first application. According to one embodiment, the instructions may, when executed by the processor, cause the electronic device to generate a prompt text requesting a summary of the first notification data received during the specified time when the number of notification messages grouped by the specific condition through the first application exceeds a specified number of times within the specified time. According to one embodiment, the instructions may, when executed by the processor, cause the electronic device to transmit the prompt generated through the first application as an input value to the artificial intelligence engine to receive a summary message based on the first notification data from the artificial intelligence engine.According to one embodiment, the instructions may, when executed by the processor, cause the electronic device to transmit the summary message to a second application that processes a notification output related to the first application. According to one embodiment, the instructions may, when executed by the processor, cause the electronic device to output the summary message to the display through the second application.

[0254] The commands according to one embodiment may cause the communication module to transmit notification data received from the external device to the first application instead of transmitting it to the second application.

[0255] According to one embodiment, the second application may include a notification manager and a notification system that handle notification scheduling and notification methods.

[0256] The specific condition according to one embodiment may include at least one of notifications containing the same device identification information, notifications received within a preset time, notifications preset as related events, and notifications repeated a preset number of times.

[0257] The instructions according to one embodiment allow the electronic device to display a notification message based on notification data received from each external device on the display, and to collect and learn user behavior pattern data regarding the displayed notification message and store user behavior pattern data by notification type.

[0258] User behavior pattern data according to one embodiment may include at least one of a behavior pattern of checking a notification message, a behavior pattern of ignoring a notification message, and a behavior pattern of deleting a notification message.

[0259] According to one embodiment, the commands allow the electronic device to identify a user's behavioral pattern related to the type of first notification data included in the summary message, and if the user's behavioral pattern learned regarding the first notification data has a behavioral pattern of ignoring or deleting, the notification output frequency or notification time interval of the summary message may be reduced.

[0260] The commands according to one embodiment may cause the electronic device to increase the priority of the summary message when the user's behavior pattern learned for the first notification data has a behavior pattern confirmed by the electronic device.

[0261] The commands according to one embodiment allow the electronic device to display the higher priority notification message at the top of other notification messages through the second application.

[0262] According to one embodiment, the summary message may include an indicator object indicating that the message is regenerated by summarizing and integrating a plurality of notification messages, and an extension object displaying individual notification messages that include the summary message.

[0263] The commands according to one embodiment may cause the electronic device to display a list of individual notification messages at the bottom of the summary message based on an input selecting the extension object.

[0264] An electronic device according to one embodiment may further include a sensor module comprising at least one sensor.

[0265] The commands according to one embodiment may enable the electronic device to check the state of the electronic device, including at least one of a do not disturb mode state, a battery state, or a screen state, recognize the current situation based on sensor data transmitted from the sensor module, and determine a real-time notification, a notification after delay, or a summary integrated notification of the summary message based on the state of the electronic device and the currently recognized situation.

[0266] According to one embodiment, the commands may cause the electronic device to output the summary message to the display when it decides to notify the summary message after a delay, based on the arrival of the time scheduled by the notification after the delay or the change of the currently recognized situation to a situation where notification is possible.

[0267] A method for managing notifications of IoT devices of an electronic device according to one embodiment may include an operation of receiving notification data regarding the status of an external device from each external device through a communication circuit. A method according to one embodiment may include an operation of collecting notification data received from each external device through a first application that manages external devices connected to the electronic device. A method according to one embodiment may include an operation of grouping the collected notification data by specific conditions through the first application. A method according to one embodiment may include an operation of generating a prompt that integrates and summarizes the first notification data received during the specified time when the notification messages grouped by the specific conditions through the first application exceed a specified number of times within a specified time. A method according to one embodiment may include an operation of receiving a summary message based on the first notification data from the artificial intelligence engine by transmitting the prompt generated through the first application as an input value to the artificial intelligence engine. A method according to one embodiment may include an operation of transmitting the summary message to a second application that processes notification outputs through the first application. A method according to one embodiment may include an operation of outputting the summary message to a display through the second application.

[0268] The operation of collecting notification data received from at least one external device according to one embodiment further includes the operation of displaying a notification message based on the notification data received from each external device on the display, and the operation of collecting and learning user behavior pattern data for the displayed notification message and storing user behavior pattern data by notification type, wherein the user behavior pattern data may include at least one of a behavior pattern of checking the notification message, a behavior pattern of ignoring the notification message, and a behavior pattern of deleting the notification message.

[0269] A notification management method for IoT devices of an electronic device according to one embodiment may further include: an operation to check a user's behavior pattern related to the type of first notification data included in the summary message; an operation to decrease the notification output frequency or notification time interval of the summary message when the user's behavior pattern learned regarding the first notification data has a behavior pattern of ignoring or deleting; and an operation to increase the display priority of the summary message when the user's behavior pattern learned regarding the first notification data has a behavior pattern of confirming.

[0270] A notification management method for IoT devices of an electronic device according to one embodiment may further include, after the operation of outputting the summary message to a display, the operation of displaying a list of individual notification messages at the bottom of the summary message based on an input selecting the extension object.

[0271] A notification management method for IoT devices of an electronic device according to one embodiment may further include checking the state of an electronic device including at least one of a do not disturb mode state, a battery state, or a screen state, recognizing the current situation based on sensor data transmitted from a sensor module, and determining real-time notification, notification after delay, or summary integrated notification of the summary message based on the state of the electronic device and the currently recognized situation.

[0272] A non-transitory computer-readable medium storing instructions that cause the processor to perform operations when executed by a processor of an electronic device according to one embodiment may store instructions that cause the processor to perform an operation of receiving notification data regarding the status of an external device from each external device through a communication circuit. A recording medium according to one embodiment may store instructions that cause the operation of collecting notification data received from each external device to be performed through a first application that manages external devices connected to the electronic device. A recording medium according to one embodiment may store instructions that cause the operation of grouping the collected notification data according to specific conditions to be performed through the first application. A recording medium according to one embodiment may store instructions that cause the operation of generating prompt text to request a summary of the first notification data received during the specified time to be performed when the number of notification messages grouped according to the specific conditions through the first application exceeds a specified number of times within a specified time. A recording medium according to one embodiment may store a command to perform an operation of receiving a summary message based on first notification data from the artificial intelligence engine by transmitting a prompt text generated through the first application as an input value to the artificial intelligence engine. A recording medium according to one embodiment may store a command to perform an operation of transmitting the summary message to a second application that processes notification output related to the first application. A recording medium according to one embodiment may store a command to perform an operation of outputting the summary message to a display through the second application.

[0273] The 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" each may 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.

[0274] The term “module” as used in the 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).

[0275] One embodiment of the present document may be implemented as software (e.g., program (140)) comprising one or more instructions stored in a storage medium (e.g., internal memory (136) or external memory (138)) readable by a machine (e.g., electronic device (101)). For example, a processor (e.g., processor (120)) of the machine (e.g., electronic device (101)) may call at least one of the one or more instructions stored in 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.

[0276] According to one embodiment, the method according to the embodiments disclosed herein may be provided by being 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.

[0277] According to one embodiment, 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 one embodiment, 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 components of the multiple components in the same or similar manner as those performed by the corresponding components among the multiple components prior to integration. According to one embodiment, 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, display; A communication circuit comprising at least one communication circuit; At least one processor including processing circuitry; and It includes a memory that stores executable instructions that can be executed by at least one processor, and When the above instructions are executed by the processor, the electronic device, Notification data regarding the status of external devices is received from each external device through the communication circuit, and Through a first application that manages external devices connected to an electronic device, notification data received from each of the external devices is collected, and Through the first application above, collected notification data is grouped according to specific conditions, and If the number of notification messages grouped by the specific conditions through the first application exceeds a specified number of times within a specified time, a prompt text is generated to request a summary of the first notification data received during the specified time, and The prompt text generated through the first application is transmitted as an input value to the artificial intelligence engine, and a summary message is received from the artificial intelligence engine based on the first notification data, and The summary message is transmitted to a second application that processes notification output related to the first application, and An electronic device that outputs the summary message to the display through the second application.

2. In Paragraph 1, The above commands cause the communication circuit to transmit notification data received from the external device to the first application instead of to the second application, and The above-mentioned second application is an electronic device comprising a notification manager and a notification system that handles notification scheduling and notification methods.

3. In Paragraph 1, The above specific conditions are, An electronic device comprising at least one of notifications containing identical device identification information, notifications received within a preset time, notifications preset as correlation events, and notifications repeated a preset number of times.

4. In Paragraph 1, The above commands, the electronic device, Notification messages based on notification data received from each external device are displayed on the display, and Collect and learn user behavior pattern data for the notification messages displayed above, and store user behavior pattern data by notification type. The above user behavior pattern data comprises at least one of a behavior pattern of checking a notification message, a behavior pattern of ignoring a notification message, and a behavior pattern of deleting a notification message.

5. In Paragraph 4, The above commands are for the electronic device, Identify user behavior patterns related to the types of first notification data included in the summary message above, and An electronic device that reduces the notification output frequency or notification time interval of the summary message when the user's behavior pattern learned from the first notification data has a behavior pattern of ignoring or deleting.

6. In Paragraph 5, The above commands are for the electronic device, An electronic device that increases the priority of the summary message when the behavioral pattern of a user learned from the first notification data has a confirmed behavioral pattern.

7. In Paragraph 6, The above commands are for the electronic device, An electronic device that displays the notification message with the highest priority above other notification messages through the second application.

8. In Paragraph 1, An electronic device comprising an indicator object indicating that the above summary message is a message regenerated by summarizing and integrating multiple notification messages, and an extension object displaying individual notification messages including the summary message.

9. In Paragraph 8, The above commands are for the electronic device, An electronic device that displays a list of individual notification messages at the bottom of the summary message based on an input selecting the above-mentioned extension object.

10. In Paragraph 1, Includes additional sensors, The above commands are for the electronic device, Checking the state of an electronic device including at least one of a Do Not Disturb mode state, a battery state, or a screen state, and recognizing the current situation based on sensor data transmitted from the sensor, An electronic device that determines real-time notification, notification after delay, or summary integrated notification of the summary message based on the state of the electronic device and the currently recognized situation.

11. In Paragraph 1, The above commands are for the electronic device, An electronic device that outputs the summary message to the display based on the arrival of the time scheduled by the notification after delay, or the change of the currently recognized situation to a situation where notification is possible, when it is decided to notify the summary message after a delay.

12. In a method for managing notifications of IoT devices of electronic devices, The operation of receiving notification data regarding the status of external devices from each external device via a communication circuit; The operation of collecting notification data received from each external device through a first application that manages external devices connected to an electronic device; An operation of grouping collected notification data according to specific conditions through the first application above; If the number of notification messages grouped by the specific conditions through the first application exceeds a specified number of times within a specified time, the operation of generating a prompt text to request a summary of the first notification data received during the specified time; The operation of transmitting a prompt text generated through the first application as an input value to an artificial intelligence engine and receiving a summary message from the artificial intelligence engine based on first notification data; The operation of transmitting the summary message to a second application that processes notification output related to the first application; and A method including the operation of outputting the summary message to a display through the second application.

13. In Paragraph 12, The operation of collecting notification data received from the above external device is, The operation of displaying a notification message based on notification data received from each external device on the display; and It further includes the operation of collecting and learning user behavior pattern data for the notification messages displayed above and storing user behavior pattern data by notification type, The above user behavior pattern data includes at least one of a behavior pattern of checking a notification message, a behavior pattern of ignoring a notification message, and a behavior pattern of deleting a notification message.

14. In Paragraph 13, An action to identify a user's behavioral pattern related to the types of first notification data included in the summary message above; If the user's behavior pattern learned from the first notification data has a behavior pattern of ignoring or deleting, an action of reducing the notification output frequency or notification time interval of the summary message; and A method further comprising an action of increasing the display priority of the summary message when the behavioral pattern of the user learned for the first notification data has a confirmed behavioral pattern.

15. In a non-transitory computer-readable medium storing instructions that cause the processor to perform operations when executed by the processor of an electronic device, said operations are, The operation of receiving notification data regarding the status of external devices from each external device via a communication circuit; An operation of collecting notification data received from each of the external devices through a first application that manages external devices connected to an electronic device; An operation of grouping collected notification data according to specific conditions through the first application above; If the notification messages grouped by the specific conditions through the first application exceed a specified number of times within a specified time, the operation of generating a prompt that integrates and summarizes the first notification data received during the specified time; The operation of transmitting a prompt generated through the first application as an input value to an artificial intelligence engine and receiving a summary message from the artificial intelligence engine based on first notification data; The operation of transmitting the summary message to a second application that processes notification output through the first application; A recording medium including the operation of outputting the summary message to a display through the second application.

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