Apparatus and method for providing guidance on path information in electronic device, and storage medium therefor

Abstract

This electronic device comprises: a communication circuit; a memory including one or more storage media for storing instructions; and at least one processor including a processing circuit, wherein the instructions, when individually or collectively executed by the at least one processor, cause the electronic device to perform the following operations of: determining a moving path on the basis of destination information; acquiring situation data on the determined moving path from one or more servers connected through a network through the communication circuit, the situation data including image data captured at at least one specific point of the determined moving path; analyzing the acquired situation data in an artificial intelligence model to generate summary information of the determined moving path; and displaying the generated summary information on a path guidance screen for the determined moving path.

Description

Device, method and storage medium for guiding route information in an electronic device

[0001] The present disclosure relates to a device, method and storage medium for guiding route information of a vehicle in an electronic device.

[0002] Wireless communication technologies are positively impacting the development of various data-driven industries. One example is the navigation function available on mobile devices. Simply entering a destination allows the user to recommend a route based on distance, cost, and traffic volume.

[0003] In addition to providing route guidance on the screen, the above navigation function also provides fragmented visual information to identify congestion along the route. This only allows drivers to recognize that congestion is occurring in a specific section, but does not provide detailed information.

[0004] The above information may be provided as background information to aid in understanding this document. None of the above is claimed to be prior art related to this document or can be used to determine prior art.

[0005] In various embodiments of the present disclosure, a device and an operating method thereof can be provided that analyze and guide traffic conditions for an expected vehicle driving route to a destination based on AI in an electronic device.

[0006] According to one embodiment, an electronic device may include a communication circuit. The electronic device may include a memory including one or more storage media for storing instructions. The electronic device may include at least one processor including a processing circuit. When the instructions are individually or collectively executed by the at least one processor, the instructions may cause the electronic device to perform at least one operation. The at least one operation may include determining a movement path based on destination information. The at least one operation may include obtaining contextual data regarding the determined movement path from one or more servers connected to a network via the communication circuit. The contextual data may include image data captured at at least one specific point along the determined movement path. The at least one operation may include analyzing the contextual data in an artificial intelligence (AI) model to generate summary information regarding the determined movement path. The at least one operation may include displaying the generated summary information on a route guidance screen for the determined movement path.

[0007] According to one embodiment, an electronic device may include a communication circuit. The electronic device may include a memory including one or more storage media for storing instructions. The electronic device may include at least one processor including a processing circuit. When the instructions are individually or collectively executed by the at least one processor, the instructions may cause the electronic device to perform at least one operation. The at least one operation may include determining a movement path of a vehicle based on destination information. The at least one operation may include obtaining situation data regarding the determined movement path from one or more servers connected to a network via the communication circuit. Here, the situation data may include image data captured at at least one specific point of the determined movement path. The at least one operation may include generating a pre-script by analyzing the obtained situation data in an artificial intelligence (AI) model. The at least one operation may include an operation for generating a prompt inquiring about traffic and / or road conditions regarding the determined travel route by considering at least one of the determined travel route or the generated pre-script in the AI ​​model. The at least one operation may include an operation for analyzing traffic and / or road conditions regarding the determined travel route based on the generated pre-script and / or the acquired situation data in response to the generated prompt in the AI ​​model, and outputting a response result based on the analysis.

[0008] According to one embodiment, a method of operating an electronic device may be provided. The method may include an operation of determining a movement path of a vehicle based on destination information. The method may include an operation of determining a movement path based on the destination information. The method may include an operation of obtaining situational data regarding the determined movement path from one or more servers connected to a network. The situational data may include image data captured at at least one specific point of the determined movement path. The method may include an operation of analyzing the situational data in an artificial intelligence (AI) model to generate summary information regarding the determined movement path. The method may include an operation of displaying the generated summary information on a route guidance screen for the determined movement path.

[0009] According to one embodiment, a method of operating an electronic device may be provided. The method may include an operation of determining a movement path of a vehicle based on destination information. The method may include an operation of obtaining situation data regarding the determined movement path from one or more servers connected to a network. Here, the situation data may include an operation of including image data captured at least at one specific point of the determined movement path. The method may include an operation of analyzing the obtained situation data in an artificial intelligence (AI) model to generate a pre-script. The method may include an operation of generating a prompt in the AI ​​model that inquires about traffic and / or road conditions regarding the determined movement path, taking into account at least one of the determined movement path or the generated pre-script. The method may include an operation of analyzing the traffic and / or road conditions regarding the determined movement path based on the generated pre-script and / or the acquired situation data in response to the generated prompt in the AI ​​model, and outputting a response result based on the analysis.

[0010] According to one embodiment, a storage medium storing computer-readable instructions may be provided. The instructions, when executed by at least a portion of at least one processor of an electronic device, may cause the electronic device to perform at least one operation. The at least one operation may include determining a movement path of a vehicle based on destination information. The at least one operation may include obtaining situational data regarding the determined movement path from one or more servers connected to a network. Here, the situational data may include image data captured at at least one specific point of the determined movement path. The at least one operation may include causing an artificial intelligence (AI) model to analyze the obtained situational data and generate a pre-script. The at least one operation may include causing the AI ​​model to generate a prompt inquiring about traffic and / or road conditions regarding the determined movement path, taking into account at least one of the determined movement path or the generated pre-script. The at least one action may include an action to analyze traffic and / or road conditions related to the determined movement path based on the generated pre-script and / or the acquired situation data in response to the generated prompt in the AI ​​model, and output a response result according to the analysis.

[0011] The technical problems to be achieved in the present disclosure are not limited to the technical problems mentioned above, and other technical problems not mentioned above can be derived from the exemplary embodiments of the present disclosure by a person having ordinary knowledge in the relevant technical field.

[0012] The effects that can be achieved by the exemplary embodiments of the present disclosure can be clearly derived and understood by those skilled in the art to which the exemplary embodiments of the present disclosure pertain, from the following description. In other words, unintended effects resulting from the implementation of the exemplary embodiments of the present disclosure can also be derived by those skilled in the art from the exemplary embodiments of the present disclosure.

[0013] In connection with the description of the drawings, the same or similar reference numerals may be used for the same or similar components.

[0014] FIG. 1 is a block diagram of an exemplary electronic device capable of performing the operations described herein.

[0015] Figure 2 is a conceptual diagram of the operation of an AI model in an electronic device according to one embodiment.

[0016] FIG. 3 is a conceptual diagram of an AI model for guiding traffic and / or road conditions of a moving path in an electronic device according to one embodiment.

[0017] FIG. 4 is a diagram illustrating a configuration of an AI model for guiding traffic and / or road conditions of a moving path in an electronic device according to one embodiment.

[0018] FIG. 5 is a control flowchart for guiding a situation (e.g., traffic situation and / or road situation) regarding a moving path in an electronic device according to one embodiment.

[0019] FIG. 6 is an example diagram of requesting image data in an electronic device according to one embodiment.

[0020] FIG. 7 is a signal flow diagram for an electronic device according to one embodiment to obtain image data from a server.

[0021] FIG. 8a is an example diagram of collecting image data from a camera installed on a road in a server according to one embodiment.

[0022] FIG. 8b is an example diagram of collecting image data from a camera installed in another vehicle by a server according to one embodiment.

[0023] FIG. 9 is an example diagram for determining a request section of image data for each target server in an electronic device according to one embodiment.

[0024] FIG. 10 is a control flowchart for guiding a situation (e.g., traffic situation and / or road situation) regarding a moving path in an electronic device according to one embodiment.

[0025] FIG. 11A is an example diagram of a user interface that summarizes and provides status information for an entire movement path in an electronic device according to one embodiment.

[0026] FIG. 11b is an example diagram of a user interface that provides status information on a congested section of a moving path in an electronic device according to one embodiment.

[0027] FIG. 11c is an example diagram of a user interface that summarizes and provides road condition information for a moving path in an electronic device according to one embodiment.

[0028] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings so that those skilled in the art can easily implement the present disclosure. However, the present disclosure may be implemented in various different forms and is not limited to the embodiments described herein. In connection with the description of the drawings, the same or similar reference numerals may be used for identical or similar components. Furthermore, in the drawings and related descriptions, descriptions of well-known functions and configurations may be omitted for clarity and conciseness.

[0029] FIG. 1 is a block diagram of an exemplary electronic device (100) capable of performing the operations described in this document.

[0030] Referring to FIG. 1, the electronic device (100) may be one of various forms of electronic devices, such as a notebook (190), smartphones (191) having various form factors (e.g., a bar-type smartphone (191-1), a foldable-type smartphone (191-2), or a sliderable (or rollable) type smartphone (191-3)), a tablet (192), a cellular phone (not shown), and other similar computing devices (not shown). The components, their relationships, and their functions illustrated in FIG. 1 are exemplary only and do not limit the implementations described or claimed in this document. The electronic device (100) may be referred to as a mobile device, a user device, a multi-function device, a portable device, or a server.

[0031] The electronic device (100) may include components including at least one processor (110) (hereinafter, referred to as 'processor (110)'), at least one memory (120) (hereinafter, referred to as 'memory (120)'), at least one display (140) (hereinafter, referred to as 'display (140)'), at least one image sensor (150) (hereinafter, referred to as 'image sensor (150)'), at least one communication circuit (160) (hereinafter, referred to as 'communication circuit (160)'), and / or at least one sensor (170) (hereinafter, referred to as 'sensor (170)'). The components are merely exemplary. For example, the electronic device (100) may include other components (e.g., power management integrated circuitry (PMIC), audio processing circuitry, an antenna, a rechargeable battery, or an input / output interface). For example, some components may be omitted from the electronic device (100). For example, several components can be combined into one component.

[0032] The processor (110) may be implemented as one or more IC (integrated circuit (or circuitry)) chips and may perform various data processing. The processor (110) may include at least one electrical circuit and may individually or collectively perform distributed processing of instructions (or programs, data, etc.) stored in the memory (120). The processor (110) may include a processor assembly including one or more processing circuits. The processor (110) may include any processing circuit operative to control the performance and operations of one or more components (e.g., the memory (120), the display (140), the image sensor (150), the communication circuit (160), and / or the sensor (170)) of the electronic device (100). For example, the processor (110) (e.g., an application processor (AP)) may be implemented as a system on chip (SoC) (e.g., a single chip or chipset). For example, the processor (110) may be implemented with multiple cores (or at least one core circuit), multiple chips, or multiple chipsets. For example, the processor (110) may include one or more processing circuits. For example, the processor (110) may include one or more processing circuits configured to individually and / or collectively perform various functions of the present disclosure. As a non-limiting example, at least a portion of the processor (110) may be included in a first chip of the electronic device (100), and at least another portion of the processor (110) may be included in a second chip of the electronic device (100) that is different from the first chip of the electronic device (100).

[0033] For example, the processor (110) may include a central processing unit (CPU) (111), a graphics processing unit (GPU) (112), a neural processing unit (NPU) (113), an image signal processor (ISP) (114), a display controller (115), a memory controller (116), a storage controller (117), a communication processor (CP) (118), and / or a sensor interface (119). These components of the processor (110) are merely exemplary. For example, the processor (110) may further include other components. For example, some components of the processor (110) may be omitted from the processor (110). For example, some components of the processor (110) may be included as separate components of the electronic device (100) outside the processor (110). For example, some components of the processor (110) (e.g., memory controller (116)) may be included within other components (e.g., at least a portion of memory (120), an interface (e.g., available for connection to at least one component of the electronic device (100)), a display (140) and / or an image sensor (150)).

[0034] The processor (110) may cause other components of the electronic device (100) to perform various operations by executing instructions stored in the memory (120). The CPU (111) (or central processing circuit) may be configured to control components of the processor (110) based on the execution of instructions stored in the memory (120) (e.g., volatile memory (121) and / or non-volatile memory (122)). The GPU (112) (or graphics processing circuit) may be configured to execute parallel operations (e.g., rendering). The NPU (113) (or neural processing circuit, or artificial intelligence (AI) chip) may be configured to execute operations for an AI model (e.g., convolution computation). The ISP (114) (or image signal processing circuit) may be configured to process a raw image acquired through the image sensor (150) into a format suitable for a component within the electronic device (100) or a component of the processor (110). The display controller (115) (or display control circuit, or DPU (display processing unit)) may be configured to process an image acquired from the CPU (111), GPU (112), ISP (114), or memory (120) (e.g., volatile memory (121)) into a format suitable for the display (140). The memory controller (116) (or memory control circuit) may be configured to control reading data from the volatile memory (121) and writing data to the volatile memory (121). The above storage controller (117) (or storage control circuit) may be configured to control reading data from the non-volatile memory (122) and writing data to the non-volatile memory (122).The CP (118) (communication processing circuit) may be configured to process data obtained from a component of the processor (110) into a format suitable for transmitting to another electronic device via the communication circuit (160), or to process data obtained from another electronic device via the communication circuit (160) into a format suitable for processing by a component of the processor (110). For example, the communication circuit (160) may include one or more communication circuits. The sensor interface (119) (or sensing data processing circuit, sensor hub) may be configured to process data on the state of the electronic device (100) and / or the state of the surroundings of the electronic device (100), obtained via the sensor (170), into a format suitable for a component of the processor (110).

[0035] The memory (120) may include one or more storage media (or one or more storage devices). For example, the memory (120) may include a memory assembly including one or more storage media. For example, the one or more storage media may include permanent memory (e.g., non-volatile memory (122)) such as a hard drive, flash memory, read-only memory (ROM), semi-permanent memory (e.g., volatile memory (121)) such as random access memory (RAM), any other suitable type of storage (or storage assembly), or any combination thereof. The memory (120) may include a cache memory, which is one or more different types of memory used to temporarily store data for a function or feature of the electronic device (100). As a non-limiting example, the cache memory may be included within the processor (110). The memory (120) may be fixedly embedded within the electronic device (100) or incorporated into one or more suitable types of components (e.g., a subscriber identity module (SIM) card and / or a secure digital (SD) card) that may be repeatedly inserted into and removed from the electronic device (100).

[0036] For example, the memory (120) may store one or more software applications, such as an operating system (or system) software application, a firmware software application, a driver software application, a plug-in (e.g., add-in, add-on, and / or applet) software application, and / or any other suitable software applications. For example, the one or more software applications may include instructions executable by the processor (110). For example, the memory (120) may store instructions callable by an application programming interface (API). For example, the memory (120) may store instructions within a library.

[0037] FIG. 2 is a conceptual diagram of an operation of an AI model in an electronic device (e.g., the electronic device (100) of FIG. 1) according to one embodiment, and FIG. 3 is a conceptual diagram of an AI model for guiding traffic and / or road conditions of a moving route in an electronic device (e.g., the electronic device (100) of FIG. 1) according to one embodiment. In FIG. 2, one AI model (250) is assumed, but more AI models may be provided. The electronic device (100) may be a single device that individually generates a moving route and / or provides a route guidance function that guides a moving route. For example, the electronic device (100) may be a composite device in which multiple devices are linked to provide a route guidance function. In the following description, it will be assumed that the electronic device (100) providing the route guidance function is configured as a single device, but is not limited thereto.

[0038] Referring to FIG. 2 or FIG. 3, the electronic device (100) may include a processor (210) (e.g., the processor (110) of FIG. 1), a memory (230) (e.g., the memory (120) of FIG. 1), and / or an interface (IF) (220) (e.g., the display (140) of FIG. 1). The electronic device (100) may include a communication circuit (240). The electronic device (100) may be a device for providing a service linked to at least one AI model (250).

[0039] The processor (210) may execute software (e.g., a program) to control at least one other component (e.g., a hardware or software component) of the electronic device (100) that is electrically connected thereto. The processor (210) may perform various data processing or operations. As at least a part of the data processing or operations, the processor (210) may store commands or data received from other components (e.g., the I / F (220)) in a memory (230) (e.g., a volatile memory, but without limitation). As at least a part of the data processing or operations, the processor (210) may process commands or data stored in the memory (230) (e.g., a volatile memory, but without limitation). As at least a part of the data processing or operations, the processor (210) may store data resulting from processing commands or data in the memory (230) (e.g., a non-volatile memory, but without limitation). The above processor (210) may include, but is not limited to, a CPU (211) (e.g., CPU (111) of FIG. 1), an NPU (213) (e.g., NPU (113) of FIG. 1), and / or a GPU (215) (e.g., GPU (112) of FIG. 1), which includes a processing circuit.

[0040] The memory (230) may store various data used by at least one component (e.g., processor (210) and / or I / F (220)) of the electronic device (100). The data may include, for example, software (e.g., program) and input data or output data for commands related thereto. The memory (230) may include volatile memory and / or non-volatile memory. The memory (230) may include a hard disk, ROM, RAM, cache memory, and / or registers, and there is no limitation on its implementation. Some of the above-described entities (e.g., registers, but there is no limitation) may be implemented as a part of the processor (210), and there is no limitation on the form of implementation. At least one AI model (e.g., AI model (250)) for instance execution may be stored in the memory (230).

[0041] The memory (230) can store at least one instruction. The processor (210) can execute at least one instruction stored in the memory (230). The at least one instruction, when executed by the processor (210), can cause the electronic device (100) to perform at least one operation. For example, as the at least one instruction is executed by the processor (210), at least one other component may be controlled, and / or various data processing or calculations may be performed. The performance of one operation by the processor (210) may mean, for example, that the operation is performed by (or under the control of) one entity included in the processor (210) (for example, the main processor, but without limitation). The performance of one operation may mean, for example, that a specific operation is performed by (or under the control of) multiple entities (for example, multiple processors). The performing of multiple operations may mean, for example, that the multiple operations are all performed by (or under the control of) a single entity (e.g., but not limited to, the main processor). The performing of multiple operations may mean, for example, that some of the multiple operations are performed by at least one entity, and some of the remaining operations are performed by at least one other entity. At least one instruction causing the performance of one or more operations may be stored, for example, in a single memory, or may be stored distributedly in each of a plurality of memories.

[0042] The at least one AI model (250) may generate a result (e.g., content such as text, images, or videos) in response to a specific command or question. A prompt may correspond to a command or question input to the at least one AI model (250). The prompt may be a medium that guides the at least one AI model (250) toward a desired task or result. The prompt may be the only window through which a user can communicate with the at least one AI model (250). The prompt may be a natural language text requesting the at least one AI model (250) to perform a specific task. The prompt (250) needs to be clear and specific in order to obtain an answer from the AI ​​model (250) that is close to the desired result. The prompt may be modified or regenerated, for example, through learning using deep learning technology based on the user's input data.

[0043] The above AI models can create new content such as stories, conversations, videos, images, or music. For example, generative AI models are based on large-scale machine learning (ML) models that use deep neural networks pre-trained on massive amounts of data.

[0044] The above-described at least one AI model (250) may be based on natural language processing (NLP) technology. The NLP technology is, for example, a technology that allows the electronic device (100) to understand or process a user's input, i.e., natural language that can be expressed in voice and / or text.

[0045] The electronic device (100) can understand natural language through NLP, and based on this, can identify human intent or convey information in a language that humans can understand. To understand human language, the NLP can learn the order of words or tokens and predict the probability of the next word or token in a given text. The token is a basic unit for processing or understanding prompts in the AI ​​model (250). The NLP can provide key functions such as tokenization, part-of-speech tagging, syntax analysis, named entity recognition, or sentiment analysis of user input data.

[0046] The at least one AI model (250) may share resources (e.g., data processing or computational power) corresponding to part or all of at least one processor included in the processor (210) and / or resources (e.g., data recording area) corresponding to part or all of the memory (230). For example, the at least one AI model (250) may be operated by at least one of the CPU (211), the NPU (213), and the GPU (215). The at least one AI model (250) may be allocated at least a portion of the memory (230) and executed solely by the CPU (211). The at least one AI model (250) may be allocated at least a portion of the memory (230) and executed solely by the NPU (213). The at least one AI model (250) may be allocated at least a portion of the memory (230) and executed solely by the GPU (215). The at least one AI model (250) may be performed by the CPU (211) and the NPU (213) in cooperation, for example, by being allocated at least a portion of the memory (230). The at least one AI model (250) may be performed by the CPU (211) and the GPU (215) in cooperation, for example, by being allocated at least a portion of the memory (230). The at least one AI model (250) may be performed by the NPU (213) and the GPU (215) in cooperation, for example, by being allocated at least a portion of the memory (230). The at least one AI model (250) may be performed by the CPU (211), the NPU (213), and the GPU (215) in cooperation, for example, by being allocated at least a portion of the memory (230).The various embodiments described later in this disclosure are not limited to the combination of components for performing at least one AI model (250), and may be implemented and / or applied based on any combination.

[0047] The electronic device (100) can operate an on-device AI model. The electronic device (100) operating the on-device AI model can perform machine learning on its own. The machine learning may be performed, for example, through a separate external server based on a network environment. In this case, 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.

[0048] The at least one AI model (250) may include a plurality of artificial neural network layers. The artificial neural network may be one of a deep neural network (DNN), a convolutional neural network (CNN), a recurrent neural network (RNN), a restricted Boltzmann machine (RBM), a deep belief network (DBN), a bidirectional recurrent deep neural network (BRDNN), deep Q-networks, or a combination of two or more of the above, but is not limited to the examples described above. The at least one AI model (250) may additionally or alternatively include a software structure in addition to a hardware structure.

[0049] The at least one AI model (250) may be trained on specified data. The at least one AI model (250) may acquire input data and perform operations based on the acquired input data to generate output data. The at least one AI model (250) may be a generative AI model. The generative AI model may produce text, images, or other media in response to a user's input based on the learned information.

[0050] According to an example, the AI ​​model (250) may be generated through machine learning. The AI ​​model (250) may include an LLM (310) or an LVM (large vision model) (320). The LLM (310) is an extended concept of a language model (LM), and corresponds to an AI model that processes natural language based on prior learning and can understand complex language patterns to generate meaningful content. The LVM (320) corresponds to an AI model that can analyze visual data based on prior learning and generate new content based on the same. Although not illustrated, the AI ​​model (250) may also include an LMM (large multimodal model). The LMM may be an AI model that can learn relationships between data of various modalities, such as text, images, videos, and audio, and perform transformation based on the relationships.

[0051] The above I / F (220) can receive destination information (260) for route guidance from a user as a prompt corresponding to the input and transmit the information to the processor (210). Although not shown, the I / F (220) can also receive departure information for route guidance from a user as a prompt corresponding to the input and transmit the information to the processor (210).

[0052] The I / F (220) may receive the processing result by the AI ​​model (250) based on the user's input data (e.g., destination information (260) and / or departure information) from the processor (210), and output a response result (270) converted into a natural language in a form that can be recognized by humans (e.g., voice or text). The response result (270) may be situation data including traffic conditions and / or road conditions on a travel route that can be determined by the departure point and the destination. The I / F (220) may receive or output natural language in the form of voice and / or text through at least one component such as a keyboard, a touch panel, a display, and / or a speaker, for example.

[0053] According to an example, the processor (210) may execute at least one instruction corresponding to a route guidance application stored in the memory (230) in response to a user's request. The processor (210) may activate a navigation function or a route guidance function by executing the at least one instruction. Hereinafter, the navigation function or the route guidance function is collectively referred to as a "route guidance function."

[0054] The processor (210) can set a destination for route guidance. The destination can be set by a user, for example, or input (destination information (260)). When a destination is set, the processor (210) can determine one or more candidate routes from a starting point to the destination. The starting point can be, for example, the current location of the electronic device (100). The electronic device (100) can confirm the current location based on a GPS signal. The starting point can be set by a user, for example, or input.

[0055] The processor (210) may perform a search for one or more candidate routes to obtain route-related information. The route-related information may include, for example, departure point information, destination information, route information for each candidate route, or expected travel time for each candidate route.

[0056] The processor (210) may determine a selected route for route guidance from among one or more candidate routes. The processor (210) may determine a selected route based on preset information (e.g., priority given to highways or toll-free roads) or a user's selection. The electronic device (100) may provide route-related information corresponding to the selected route to one or more servers (hereinafter referred to as "target servers") through the communication circuit (240). The processor (210) may receive situation data according to the route-related information from the target server through the communication circuit (240). The situation data may include image data captured along the travel route. The image data may be provided, for example, by one or more cameras installed along the travel route. The image data may be provided, for example, by cameras installed in other vehicles that have driven along the travel route.

[0057] The AI ​​model (250), which partially shares the resources of the processor (210) and the memory (230), can analyze the situation data and generate analysis data based on the analysis. The analysis data may include, for example, summary information analyzed for each event on the movement path. The analysis data may include, for example, summary information organizing all events that occurred on the movement path. The analysis data may include, for example, summary information organizing all traffic conditions and / or road conditions on the movement path. The analysis data may be stored in the memory (230) in the form of a script. The script form may be a bundle or set of analysis data generated based on the results of analyzing the situation data. In the present disclosure, considering that the analysis data is in the form of a script, it is also referred to as a “pre-script.”

[0058] The above-described pre-script may be, for example, analysis data obtained or generated as a result of the analysis of a specific event situation, such as an accident, a broken-down vehicle, construction work, traffic congestion, or road damage, that occurred on the moving route based on the above-described situation data. The analysis data may be video data related to the event. The analysis data may be full or summarized video data related to events related to traffic situations, such as accidents, broken-down vehicles, or traffic congestion. The analysis data may be full or summarized video data related to events related to road situations, such as construction work or road damage. The analysis data may be text information related to the event. The analysis data may be full or summarized text information related to events related to traffic situations, such as accidents, broken-down vehicles, or traffic congestion. The analysis data may be full or summarized text information related to events related to road situations, such as construction work or road damage. The analysis data may be data (e.g., video or text information) processed from raw data at the request or need of a user. The event video data may be unprocessed raw data (e.g., video data or text information).

[0059] For example, the AI ​​model (250) may generate a response result (270) that guides the situation of the movement route in response to a predetermined question. The AI ​​model (250) may transmit the generated response result (270) to a display (e.g., the display (140) of FIG. 1) through the I / F (220). The AI ​​model (250) may transmit the generated response result to an audio signal output device such as a speaker. For example, when summary information on traffic and / or road conditions of the movement route is requested, the AI ​​model (250) may read out target analysis data from the memory (230) and output it. For example, when analysis information on a congested section is requested in text format, the AI ​​model (250) may read out analysis data on the congested section from the memory (230) and output it. For example, when information on traffic and / or road conditions of a moving route is requested, the AI ​​model (250) may read target analysis data from the memory (230), reprocess the read target analysis data, and output it.

[0060] According to an example, the electronic device (100) can execute at least one instance of an AI model. The instance may be an object corresponding to a program (or application), such as an AI model, for example. The instance may be named a replica, a pod, a container, or a virtual machine, and there is no limitation on the name thereof. The number of instances may correspond to the size of a resource (e.g., a GPU (112) or an NPU (113)), and accordingly, the number of instances may be used interchangeably with the size of the resource, or the instances may be used interchangeably with the resource.

[0061] According to one example, a plurality of user requests may be input to the electronic device (100). The user requests may be associated with a service. The user request may be processed by a first instance of a first AI model, and a first processing result may be provided from the first instance of the first AI model. The first processing result may be processed by a first instance of a second AI model, and accordingly, a second processing result may be provided by the first instance of the second AI model. By serial processing of the processing results, the first instance of the M-th AI model may receive and process the (N-1)-th processing result. The first instance of the M-th AI model may provide the N-th processing result as a response. Accordingly, a response corresponding to the user request may be provided.

[0062] Based on the above-described process, responses corresponding to each of a plurality of user requests may be provided. Meanwhile, since processing must be performed by an instance, the time for providing responses corresponding to each of a plurality of user requests (hereinafter referred to as “response time”) may take a relatively long time. The response time may affect the latency of the corresponding instance. To reduce the response time, the electronic device (100) may increase the number of instances of at least one AI model, which may be referred to as scaling out. However, there may be limitations in increasing the number of instances due to hardware and / or software constraints of the electronic device (100) and / or parameter restrictions of the AI ​​model (e.g., large language model (LLM)). In the present disclosure, for convenience of explanation, one AI model and one instance will be described assuming one, but it may be possible to configure or operate multiple AI models and / or multiple instances in consideration of a user’s request.

[0063] FIG. 4 is a diagram of an AI model for guiding traffic and / or road conditions of a moving path in an electronic device (e.g., the electronic device (100) of FIG. 1) according to one embodiment.

[0064] Referring to FIG. 4, the AI ​​model (250) may include a prompt engineering model (410), a data analysis module (420), or a recording module (430). The AI ​​model (250) may input predetermined data (e.g., expected path data (330) and / or situation data (340)). The input data may be transmitted to and processed by one of the LLMs (e.g., the LLM (310) of FIG. 3) or LVMs (e.g., the LVM (320) of FIG. 3) included in the AI ​​model (250) based on the type of data.

[0065] For example, the AI ​​model (250) may analyze situation data (340) by considering expected route data (330) for route guidance. The expected route data (330) may be data regarding a movement route acquired by a route guidance function based on destination information set for route guidance. The expected route data (330) may include, for example, departure information, destination information, movement route information, or expected travel time. For example, the situation data may be data regarding traffic conditions and / or road conditions along the movement route. The traffic conditions may correspond to situations where vehicle flow is impeded due to events such as accidents, broken-down vehicles, or traffic congestion. The road conditions may correspond to situations where vehicle flow is impeded due to events such as construction or road damage. The situation data may be data related to an event situation including traffic conditions and / or road conditions. The situation data may include, for example, image data captured at at least one specific point along the determined movement route. The above situation data may be provided by one or more servers connected to a network.

[0066] For example, the data analysis module (420) may summarize real-time traffic and / or road conditions based on the situation data and provide the summarized information to the user or driver. To this end, the data analysis module (420) may analyze the situation data and store the analysis data obtained through the analysis in the form of a script in the recording module (430). When a request is made to provide summary information on traffic and / or road conditions, the data analysis module (420) may read the corresponding analysis data from the recording module (430) and output it as a response result (350).

[0067] For example, the data analysis module (420) may provide users or drivers with detailed information on real-time traffic and / or road conditions based on the situation data. To this end, the data analysis module (420) may analyze the situation data and store the analysis data obtained through the analysis in the form of a script in the recording module (430).

[0068] The prompt engineering module (410) can generate prompts requesting the generation of detailed information regarding real-time traffic conditions and / or road conditions. The prompt engineering module (410) can, for example, generate optimal prompts based on the analysis data and route-related information generated for route guidance. The prompt engineering module (410) can transmit the generated prompts to the data analysis module (420).

[0069] The data analysis module (420) may generate detailed information regarding traffic and / or road conditions in response to the prompt. For example, the data analysis module (420) may reprocess the analysis data to generate an image of the cause and / or current situation of an event, such as a traffic jam or accident, in a specific section of the travel route. The generated image is output as a response result (350), allowing the user or driver to intuitively recognize the situation related to the event. The generated image may be, for example, 3D image data generated by reprocessing the analysis data.

[0070] FIG. 5 is a control flowchart for guiding a situation (e.g., traffic conditions and / or road conditions) regarding a movement path in an electronic device (e.g., the electronic device (100) of FIG. 1) according to one embodiment. For example, the electronic device (100) may be a single device that individually generates a movement path and / or provides a route guidance function that guides a movement path. For example, the electronic device (100) may be a composite device in which multiple devices work together to provide a route guidance function. In the following description, it will be assumed that the electronic device (100) providing the route guidance function is configured as a single device, but is not limited thereto.

[0071] Referring to FIG. 5 , the electronic device (100) may determine a movement path for route guidance in operation 510. The movement path may include both a “driving path” for a vehicle such as a bicycle, motorcycle, or automobile, or a “walking path” for a pedestrian. The route guidance may include route guidance for a vehicle or route guidance for a pedestrian. The route guidance for a vehicle may be provided, for example, by a navigation system provided by default in the vehicle and / or a separate electronic device (e.g., a navigator, smartphone, or tablet). The route guidance for a pedestrian may be provided by a mobile device (e.g., a smartphone or tablet). For convenience, the following description will be based on route guidance for a vehicle. However, the operations to be described below may also be equally applied to route guidance for pedestrians.

[0072] According to one example, when a destination is set, the electronic device (100) can determine a travel route from a starting point to a destination. The starting point may be, for example, the current location of the electronic device (100). The electronic device (100) can confirm the current location based on a GPS signal. The starting point may be set by a user, for example. The destination may be set by a user, for example.

[0073] The electronic device (100) may generate one or more candidate routes for starting from a current location and arriving at a destination. The electronic device (100) may suggest the generated one or more candidate routes to a user. The electronic device (100) may provide information regarding the one or more candidate routes (hereinafter referred to as “candidate route-related information”). To this end, the electronic device (100) may perform a search for the generated one or more candidate routes. The candidate route-related information may include, for example, departure information, destination information, movement route information for each candidate route, or an expected travel time for each candidate route. The departure information may be, for example, information that can identify the location of the departure point (e.g., latitude / longitude values, address, building name). The destination information may be, for example, information that can identify the location of the destination (e.g., latitude / longitude values, address, building name). The movement route information for each candidate route may be, for example, information that guides the corresponding candidate route on a map. The estimated travel time for each candidate route may be, for example, the estimated travel time considering the current traffic situation when using the candidate route. If there are one or more waypoints set by the user's request, the candidate route-related information may include waypoint information for the one or more waypoints or the estimated travel time to each waypoint. The candidate route-related information may include traffic information for each section of each candidate route. The candidate route-related information may include information regarding a specific event situation (e.g., an accident situation or a construction situation) on each candidate route. The information regarding the specific event situation may be, for example, an announcement message such as, "Congestion due to construction has occurred at point a."

[0074] The electronic device (100) may determine a movement path (hereinafter referred to as a “selected path”) to be applied for route guidance among one or more candidate paths. The electronic device (100) may determine the selected path based on preset information (e.g., priority given to highways or toll-free roads) or a user’s selection. The selected path may be a movement path for route guidance. The electronic device (100) may provide information regarding the selected path (hereinafter referred to as “path-related information”). The path-related information may include, for example, departure information, destination information, movement path information, or an expected travel time. The departure information may be, for example, information that can identify the location of the departure point (e.g., latitude / longitude values, address, building name). The destination information may be, for example, information that can identify the location of the destination (e.g., latitude / longitude values, address, building name). The movement path information may be, for example, information that guides the selected path on a map. The above-mentioned estimated travel time may be, for example, the estimated travel time considering the current traffic situation when using the selected route. The route-related information may include traffic information for each section of the selected route. The route-related information may include information regarding a specific event situation (e.g., an accident situation or a construction situation) on the selected route. The information regarding the specific event situation may be, for example, a guidance message such as, “Severe traffic congestion is occurring in section a due to an accident.” If there are one or more waypoints set by the user’s request, the route-related information may include waypoint information regarding the one or more waypoints or the estimated travel time to each waypoint.

[0075] The electronic device (100) may, when a movement path (or selection path) is determined, generate analysis data regarding the movement path in operation 520 and store the generated analysis data in the form of a script. The analysis data in the form of a script may be referred to as a “pre-script.”

[0076] The electronic device (100) may receive situational data regarding the movement path to be analyzed, which is the target of analysis, from one or more servers (hereinafter referred to as "target servers") connected via a network to generate analysis data regarding the movement path. To this end, the electronic device (100) may provide path-related information generated in response to the movement path to the target server.

[0077] For example, the electronic device (100) may determine the type of situation data to be requested from the target server. The electronic device (100) may provide unit section information for obtaining situation data to the target server. The unit section may be a portion of the movement route. The unit section may be a section of the movement route where traffic congestion occurs due to heavy traffic. The unit section may be a section of the movement route where traffic congestion occurs due to an accident. The unit section may be a section of the movement route where traffic congestion occurs due to construction. The electronic device (100) may request image data as situation data, for example. The electronic device (100) may request raw data that has not been processed into situation data, for example. To this end, the electronic device (100) may transmit path-related information about the movement route to the target server.

[0078] According to one example, the electronic device (100) may receive situation data including image data from the target server. The image data may be image data captured along the movement route. The image data may be, for example, image data captured by a fixed and / or mobile camera installed along the movement route. The image data may be, for example, image data captured by a camera of a black box installed in a vehicle that drove along the movement route. The image data may be, for example, unprocessed raw data. The unprocessed data may be one of various pieces of information, such as news, newspaper articles, content posted on SNS or portal sites, related to road conditions or traffic conditions along the movement route. The news, newspaper articles, content posted on SNS or portal sites may be, for example, unprocessed raw data. The situation data may include, for example, data regarding traffic conditions along the movement route (hereinafter referred to as “traffic condition data”) and / or data regarding road conditions (hereinafter referred to as “road condition data”). The traffic condition data may include, for example, information related to congestion along the travel route. The congestion-related information may be information providing information on congestion along each sub-route included in the travel route. The sub-route may be a route that divides the travel route into predetermined intervals. The road condition data may include, for example, road condition information along the travel route. The road condition information may be information related to potholes, cracks, or repair roads existing along the travel route. The road condition information may include, for example, location information where potholes, cracks, or repair roads exist.

[0079] The electronic device (100) may analyze situation data regarding the movement path to generate a pre-script. The situation data may include image data captured at at least one specific point of the movement path. The image data may be, for example, image data captured by one or more cameras installed at the at least one specific point. The image data may be, for example, image data captured by a camera installed in another vehicle on a road section including the at least one specific point. The road section including the at least one specific point may be a congested section of the determined movement path. As an example, the electronic device (100) may request a target server to provide video or audio content of a length corresponding to a target time interval that can be determined for each of the at least one specific point. The electronic device (100) may determine the target time interval by considering the expected time required from the current location to the at least one specific point.

[0080] The electronic device (100) may include an on-device type generative AI model (e.g., AI model (250) of FIG. 2). The on-device type generative AI model may operate to analyze the situation data and generate a dictionary script based on the analysis. For example, the electronic device (100) may be provided with a dictionary script generated by a network-based generative AI. The electronic device (100) may, for example, generate or obtain summary information analyzed for each event on the movement path as a dictionary script. The summary information for each event may be in the form of an image and / or text. The electronic device (100) may, for example, generate summary information summarizing all events that occurred on the movement path as a dictionary script. The summary information for all events may be in the form of an image and / or text. The electronic device (100) may, for example, generate summary information summarizing all traffic conditions and / or road conditions on the movement path as a dictionary script. The summary information summarizing the overall traffic situation and / or road conditions may be in the form of a video and / or text.

[0081] The above-described pre-script may be a bundle or set of analysis data generated based on the results of analyzing the above-described situation data. The above-described pre-script may be, for example, analysis data obtained or generated as a result of analyzing a specific event situation, such as an accident, a broken-down vehicle, construction work, traffic congestion, or road damage, that occurred on the moving route based on the above-described situation data. The analysis data may be video data related to the event. The analysis data may be full or summarized video data related to events related to traffic situations, such as accidents, broken-down vehicles, or traffic congestion. The analysis data may be full or summarized video data related to events related to road situations, such as construction work or road damage. The analysis data may be text information related to the event. The analysis data may be full or summarized text information related to events related to traffic situations, such as accidents, broken-down vehicles, or traffic congestion. The analysis data may be full or summarized text information related to events related to road situations, such as construction work or road damage. The analysis data may be data (e.g., video or text information) processed from raw data at the request or need of a user. The above event video data may be unprocessed raw data (e.g., video data or text information).

[0082] The electronic device (100) may, in operation 530, generate a response result that guides the situation of the movement path in response to a predetermined question. The electronic device (100) may output the generated response result as visual information through a display. The electronic device may output the generated response result as auditory information through a speaker. The electronic device may output visual information and auditory information according to the generated response result through the display or speaker, respectively.

[0083] The electronic device (100) may use analysis data stored in script form to provide analysis information related to a travel route to a driver or user. To this end, the electronic device (100) may output the analysis information as is or reprocess and output it. For example, if summary information on traffic and / or road conditions along a travel route is requested, the electronic device (100) may read and output the target analysis data from pre-stored analysis data. For example, if analysis information on a congested section is requested in text format, the electronic device (100) may read and output the analysis data related to the congested section from pre-stored analysis data.

[0084] According to one example, the electronic device (100) may generate complete information or summary information related to traffic conditions and / or road conditions of a moving route based on the stored pre-script and provide the information to the driver or user. The complete information or summary information may be image data and / or text information. The electronic device (100) may generate complete information or summary information related to a specific event based on the stored pre-script and provide the information to the driver or user. The complete information or summary information may be image data and / or text information. The traffic conditions, the road conditions, or the specific event may be the same as defined above.

[0085] According to one example, the electronic device (100) may generate a prompt to analyze the cause and / or current situation of a specific event occurring on the movement path. The electronic device (100) may generate the prompt using, for example, path-related information and / or a pre-script. In response to the prompt, the electronic device (100) may process image data included in the situation data in an AI model to generate event image data related to the specific event. The electronic device (100) may output the event image data together with text information regarding the specific event. The event image data may be three-dimensional image data generated by reprocessing an image captured by at least one camera. The specific event may include traffic congestion, an accident, or a construction situation on the determined movement path.

[0086] According to one example, the electronic device (100) may receive situation data in real time from a target server, and based on this, generate analysis information related to a movement path and provide it to a driver or a user. The electronic device (100) may, for example, generate full information or summary information related to traffic conditions and / or road conditions of a movement path based on the real-time situation data and provide the information to the driver or the user. The full information or summary information may be image data and / or text information. The electronic device (100) may, for example, generate full information or summary information related to a specific event based on the real-time situation data and provide the information to the driver or the user. The full information or summary information may be image data and / or text information. The traffic conditions, the road conditions, or the specific event may be the same as defined above.

[0087] As described above, after a user inputs a destination, the system can provide not only simple route guidance but also summarized traffic and / or road condition information to intuitively recognize special traffic and / or road conditions along the route. Furthermore, traffic and / or road condition information for sections with special traffic and / or road conditions can be provided in various formats (e.g., video or text), allowing the user to more conveniently access various information related to route guidance.

[0088] FIG. 6 is an example diagram of requesting image data from an electronic device (e.g., the electronic device (100) of FIG. 1) according to one embodiment.

[0089] Referring to FIG. 6, the electronic device (100) may determine a target time interval (Δt) for each at least one specific point from which image data is to be obtained in a movement path T (630). The movement path T (630) may be a path to be driven from a first point S (e.g., a starting point) (610) to a second point D (e.g., a destination) (620). The first point S (610) and the second point D (620) may be any points in the movement path. However, the second point D (620) must be a point that can be reached after passing the first point S (610) in the movement path T (630). The image data may be image data obtained by photographing a road condition and / or a traffic condition at the at least one specific point. The at least one specific point may be, for example, a location where a target camera (660, 670) for photographing a road condition and / or a traffic condition is installed. For example, the first camera (660) may be installed at a relatively closer distance from the electronic device (100) than the second camera (670). Image data captured by the target cameras (660, 670) may be transmitted to and stored in a single target server or an independent target server.

[0090] The electronic device (100) may determine the target time period (Δt) by considering the expected time required to the at least one specific point. The electronic device (100) may predict the expected time required using, for example, path-related information acquired for the movement path. The target time period (Δt) may determine a section of image data to be obtained from among image data captured by the target cameras (660, 670). The target time period (Δt) for the first camera (660) may be, for example, the first time period (Δt1). The target time period (Δt) for the second camera (670) may be the second time period (Δt2). Since the expected time required to the first camera (660) may be relatively shorter than the expected time required to the second camera (670), the first time period (Δt1) may be shorter than the second time period (Δt2).

[0091] The electronic device (100) may request content (e.g., image data and / or audio data) of a length corresponding to the determined target time period (Δt) from one or more target servers. The target server may exist in one of a plurality of cameras (660, 670), or may exist for each camera (660, 670). The electronic device (100) may request provision of first target image data captured by a first camera (660) and second target image data captured by a second camera (670) from at least one target server. The first target image data may be, for example, image data captured by the first camera (660) from a time point in time that regresses to the past by a first time period (Δt1) from a first current time point (t1) to the first current time point (t1). The second target image data may be, for example, image data captured by the second camera (670) from a point in time that has regressed in time by a second time interval (Δt2) from the second current point in time (t2) to the second current point in time (t2). The first current point in time (t1) or the second current point in time (t2) may be a point in time at which it is decided to request provision of image data or a point in time at which provision of image data is requested. The first current point in time (t1) may be substantially the same as the second current point in time (t2).

[0092] The electronic device (100) can acquire the first target image data and the second target image data provided by one or more target servers. The electronic device (100) can analyze the acquired first and second target image data and generate analysis data based on the analysis results. The electronic device (100) can store the analysis data in the form of a script.

[0093] In the above-described disclosure, video content is assumed, but the electronic device (100) can also receive audio content from the target server in the same or similar manner.

[0094] FIG. 7 is a signal flow diagram for an electronic device (e.g., the electronic device (100) of FIG. 1) according to one embodiment to obtain image data from a server. The electronic device (100) may provide route guidance based on a route guidance function. The server may manage data regarding traffic conditions and / or road conditions. The data regarding traffic conditions and / or road conditions may include image data captured along a moving route. In FIG. 7, only one electronic device (710) or one server (720) is assumed, but more electronic devices and / or servers may be provided.

[0095] Referring to FIG. 7, the server (720) can collect image data captured on a road it manages (operation 721). For example, the server (720) can receive image data captured by cameras installed on a road or road section it manages in real time and / or non-real time (see FIG. 8a). For example, the server (720) can receive image data captured by cameras of black boxes installed on vehicles passing through a road or road section it manages (see FIG. 8b).

[0096] The electronic device (710) may inquire of the server (720) whether video data can be provided in response to the occurrence of a predetermined event (operation 711). The predetermined event may occur when video is needed for guidance on traffic and / or road conditions based on a navigation function. For example, the electronic device (710) may inquire of the availability of video data in order to analyze real-time traffic and / or road conditions of a movement route in response to the determination of a movement route based on current location information and destination location information via GPS signals. In one example, the electronic device (710) may inquire of the server (720) whether video data can be provided for each sub-route included in the movement route. For example, the electronic device (710) may inquire of the availability of video data for each server.

[0097] The server (720) can determine whether video data can be provided to the electronic device (710) in response to an inquiry from the electronic device (710). Based on the result of the determination, the server (720) can transmit a response corresponding to the inquiry to the electronic device (710) (operation 723).

[0098] The electronic device (710) may request video data from the server (720) (operation 713). For example, the electronic device (710) may determine a playback section or playback time (e.g., target time sections (Δt1, Δt2) of FIG. 6) of the requested video data and transmit the determined playback section or playback time to the server (720). The electronic device (710) may determine the playback section or playback time based on an expected time required to move to a shooting location (e.g., a location where target cameras (660, 670) of FIG. 6 are installed).

[0099] The server (720) may generate the requested video data by considering the playback section or playback time provided by the electronic device (710) (operation 725). For example, the server (720) may generate the requested video data by extracting the video data included in the playback section or playback time from the entire video data.

[0100] The server (720) may transmit the requested image data to the electronic device (710) (operation 727). The electronic device (710) may analyze the requested image data provided from the server (720) and store the analysis data reflecting the analysis result in the form of a script. For example, the electronic device (710) may analyze real-time traffic conditions and / or road conditions using the requested image data. The electronic device (710) may generate analysis data regarding the analyzed traffic conditions and / or road conditions. The electronic device (710) may store the generated analysis data in the form of a script. When receiving an inquiry regarding the traffic conditions and / or road conditions of a moving route, the electronic device (710) may provide summary information in the form of text corresponding to the inquiry based on the analysis data stored in the form of the script, or may generate and provide processed content.

[0101] FIG. 8A is an example diagram of collecting image data from a camera (820) installed on a road in a server (e.g., server (720) of FIG. 7) according to one embodiment.

[0102] Referring to FIG. 8A, the server (720) can receive image data captured by each of one or more cameras (821, 823, 825) installed on a road or road section (810) managed by the server. For example, the multiple cameras (821, 823, 825) can capture images of different road sections and transmit the captured image data to the server (720) in real time. For example, the multiple cameras (821, 823, 825) can capture images of different road sections and transmit the captured image data to the server (720) in non-real time. For example, the multiple cameras (821, 823, 825) can capture images of different road sections and transmit the captured image data to the server (720) in real time and non-real time. The above-described captured image data may be, for example, image data that can be used to check road conditions (e.g., potholes, cracks, or road repairs) by capturing a corresponding road section. The above-described captured image data may be, for example, image data that can be used to check traffic conditions (e.g., accidents, breakdowns, or traffic congestion) by capturing vehicles operating on the corresponding road section. The image data transmitted to the server (720) by one or more cameras (821, 823, 825) may be raw data.

[0103] FIG. 8b is an example diagram of collecting image data from a camera installed in another vehicle in a server (e.g., server (720) of FIG. 7) according to one embodiment.

[0104] Referring to FIG. 8b, the server (720) can collect video data captured by cameras of vehicles (841, 843, 845, 847, 849) that drove on a specific section (830) of a road managed by the server. The specific section (830) may be a section where a predetermined event occurred. The predetermined event may include an event caused by a vehicle accident. The predetermined event may include an event caused by construction. The predetermined event may include an event caused by traffic congestion. The predetermined event may include an event caused by road damage. In addition, traffic conditions and / or road conditions on a moving route that may affect vehicle driving may be determined as the corresponding event.

[0105] The image data captured by the cameras of the above vehicles (841, 843, 845, 847, 849) may be, for example, image data that can be used to check road conditions (e.g., potholes, cracks, or road repairs) by capturing the corresponding road section. The captured image data may be, for example, image data that can be used to check traffic conditions (e.g., accidents, breakdowns, or traffic congestion) by capturing surrounding vehicles operating on the corresponding road section. The captured image data provided to the server (720) may be raw data.

[0106] For example, the server (720) may store captured image data provided by vehicles (841, 843, 845, 847, 849) that are driving or have driven on a road section (830) where an event occurred. The server (720) may store the captured image data as raw data or process and store it as needed. In order to obtain the captured image data, the server (720) may track the locations of the target vehicles (841, 843, 845, 847, 849) based on a device such as GPS. In this case, the server (720) may identify the corresponding vehicles (841, 843, 845, 847, 849). The server (720) may also directly request provision of captured image data from the identified vehicles. The above server (720) can confirm whether the vehicle has agreed to the provision of the video data before requesting the provision of the video data.

[0107] FIG. 9 is an exemplary diagram of determining a request section of image data (e.g., target time sections (Δt1, Δt2) of FIG. 6) for each target server in an electronic device (e.g., electronic device (100) of FIG. 1) according to one embodiment.

[0108] Referring to FIG. 9, the electronic device (or vehicle) (910) may determine a target time period (Δt) for each of the target servers (920, 930, 940, 950). For example, the electronic device (910) may determine the target time period (Δt) for each target server based on the expected time required to move to the shooting point. The target time periods (Δt) determined for each of the target servers (920, 930, 940, 950) may, for example, all be different or may be partially different. The target time periods (Δt) determined for each of the target servers (920, 930, 940, 950) may, for example, all be the same or may be partially the same. For example, the illustrated target time periods (Δt1, Δt2, Δt3, Δt4) may all be different. For example, the first target time period (Δt1) may determine the playback time (923) of the first target image data to be provided to the electronic device (910) among the total playback time (921) of the image data stored in the first server (920). For example, the second target time period (Δt2) may determine the playback time (933) of the second target image data to be provided to the electronic device (910) among the total playback time (931) of the image data stored in the second server (930). For example, the third target time period (Δt3) may determine the playback time (943) of the third target image data to be provided to the electronic device (910) among the total playback time (941) of the image data stored in the third server (940). For example, the fourth target time period (Δt4) may determine the playback time (953) of the fourth target image data to be provided to the electronic device (910) among the total playback time (951) of the image data stored in the fourth server (950). As an example, the playback time for each target image data may be shorter in the order of the fourth target time period (Δt4), the second target time period (Δt2), the third target time period (Δt3), and the first target time period (Δt1).

[0109] FIG. 10 is a control flowchart for providing guidance on a situation (e.g., traffic conditions and / or road conditions) regarding a movement path in an electronic device (e.g., the electronic device (100) of FIG. 1 ) according to one embodiment. For example, the electronic device (100) may be a single device that individually generates a movement path and / or provides a route guidance function that guides a movement path. For example, the electronic device (100) may be a composite device in which multiple devices work together to provide a route guidance function. In the following description, it will be assumed that the electronic device (100) providing the route guidance function is configured as a single device, but is not limited thereto.

[0110] Referring to FIG. 10, the electronic device (100) may determine a movement path for route guidance in operations 1011 to 1015 (operation 510). In operation 1011, the electronic device (100) may determine whether a route guidance function is activated. The route guidance function may be activated, for example, by executing a route guidance application installed in the electronic device (100). If the route guidance function is activated, the electronic device (100) may set a destination in operation 1013. The destination may be set, for example, by a user. The destination may be input, for example, by a user. If the destination is set, the electronic device (100) may propose one or more candidate routes from a starting point to a destination in operation 1015 so that one candidate route is selected. The starting point may be, for example, the current location of the electronic device (100). The electronic device (100) can determine the current location based on GPS signals. The starting point may be set by the user, for example. The starting point may also be input by the user, for example.

[0111] According to one example, the electronic device (100) may generate one or more candidate routes for starting from a current location and arriving at a destination. The electronic device (100) may suggest the generated one or more candidate routes to a user. The electronic device (100) may provide candidate route-related information corresponding to the one or more candidate routes. To this end, the electronic device (100) may perform a search for the generated one or more candidate routes. The candidate route-related information may include, for example, departure information, destination information, movement route information for each candidate route, or an expected travel time for each candidate route. The departure information may be, for example, information that can identify the location of the departure point (e.g., latitude / longitude values, address, building name). The destination information may be, for example, information that can identify the location of the destination (e.g., latitude / longitude values, address, building name). The movement route information for each candidate route may be, for example, information that guides the corresponding candidate route on a map. The estimated travel time for each candidate route may be, for example, the estimated travel time considering the current traffic situation when using the candidate route. If there are one or more waypoints set by the user's request, the candidate route-related information may include waypoint information for the one or more waypoints or the estimated travel time to each waypoint. The candidate route-related information may include traffic information for each section of each candidate route. The candidate route-related information may include information regarding a specific event situation (e.g., an accident situation or a construction situation) on each candidate route. The information regarding the specific event situation may be, for example, an announcement message such as, "Congestion due to construction has occurred at point a."

[0112] The electronic device (100) may determine a selected route from among one or more candidate routes. The selected route may be used as a travel route to be applied for route guidance. The electronic device (100) may determine the selected route based on preset information (e.g., priority given to highways or toll-free roads) or a user's selection. The electronic device (100) may provide route-related information corresponding to the selected route. The route-related information may include, for example, departure information, destination information, travel route information, or an expected travel time. The departure information may be, for example, information that can identify the location of the departure point (e.g., latitude / longitude values, address, building name). The destination information may be, for example, information that can identify the location of the destination (e.g., latitude / longitude values, address, building name). The travel route information may be, for example, information that guides the selected route on a map. The expected travel time may be, for example, an expected travel time considering the current traffic situation when using the selected route. The above route-related information may include traffic information for each section of the selected route. The route-related information may include information regarding a specific event (e.g., an accident or construction situation) on the selected route. The information regarding the specific event may be, for example, a guidance message such as, "Severe traffic congestion is occurring in section a due to an accident." If there are one or more waypoints set by the user's request, the route-related information may also include waypoint information regarding the one or more waypoints or the estimated travel time to each waypoint.

[0113] The electronic device (100) may store analysis data regarding the movement path in the form of a script in operations 1017 and 1019 (operation 520). The analysis data in the form of a script may be referred to as a “pre-script.” For example, the electronic device (100) may obtain situational data regarding the movement path and analyze the obtained situational data to generate the analysis data. The situational data may include image data. The image data may be image data captured along the movement path. The image data may be, for example, image data captured by a fixed and / or mobile camera installed along the movement path. The image data may be, for example, image data captured by a camera of a black box installed in a vehicle that drove along the movement path. The image data may be, for example, unprocessed raw data. The unprocessed data may be one of various pieces of information, such as news, newspaper articles, content posted on social media or portal sites, related to road conditions or traffic conditions along the movement path. The above news, newspaper articles, content posted on social media, or portal sites may be, for example, unprocessed raw data. The above situation data may include, for example, traffic situation data and / or road situation data along the travel route. The traffic situation data may include, for example, information related to congestion along the travel route. The congestion-related information may be information providing information on congestion for each sub-route included in the travel route. The sub-route may be a route that divides the travel route into predetermined intervals. The road situation data may include, for example, road condition information along the travel route. The road condition information may be information related to potholes, cracks, or repaired roads present along the travel route.The above road condition information may include, for example, location information where potholes, cracks, or repair roads exist.

[0114] According to one example, the electronic device (100) may, in operation 1017, obtain situation data regarding the movement path. For example, the electronic device (100) may receive the situation data from one or more target servers connected via a network. To this end, the electronic device (100) may provide path-related information generated in response to the movement path to the target server. The electronic device (100) may, for example, determine the type of situation data to be requested from the target server. The electronic device (100) may provide unit section information for obtaining the situation data to the target server. The unit section may be a portion of the movement path. The unit section may be a section of the movement path where traffic congestion occurs due to heavy traffic. The unit section may be a section of the movement path where traffic congestion occurs due to an accident. The unit section may be a section of the movement path where traffic congestion occurs due to construction. The electronic device (100) may, for example, request image data as situation data. The electronic device (100) may, for example, request raw data that has not been processed into situation data. To this end, the electronic device (100) may transmit path-related information about the movement path to the target server.

[0115] For example, the electronic device (100) may, in operation 1019, generate analysis data by analyzing the acquired situation data. The situation data may include image data captured at at least one specific point of the movement path. The image data may be, for example, image data captured by one or more cameras installed at the at least one specific point. The image data may be, for example, image data captured by a camera installed in another vehicle in a road section including the at least one specific point. The road section including the at least one specific point may be a traffic congestion section in the determined movement path. The electronic device (100) may, for example, request a target server for video or audio content of a length corresponding to a target time period that can be determined for each of the at least one specific point. The electronic device (100) may determine the target time period by considering an expected time required from the current location to the at least one specific point.

[0116] For example, the electronic device (100) may include an on-device type generative AI model (e.g., AI model (250) of FIG. 2). The on-device type generative AI model may operate to analyze the situation data and generate analysis data based on the analysis in the form of a script. For example, the electronic device (100) may receive analysis data generated by a network-based generative AI in the form of a script. The electronic device (100) may, for example, generate or obtain summary information analyzed for each event in the movement path in the form of a script. The type of the summary information for each event may be an image and / or text. The electronic device (100) may, for example, generate summary information summarizing all events that occurred in the movement path as analysis data. The type of the summary information for all events may be an image and / or text. The electronic device (100) may, for example, generate summary information summarizing all traffic conditions and / or road conditions of the movement path as analysis data. The type of summary information summarizing the overall traffic situation and / or road conditions may be video and / or text.

[0117] The pre-script corresponding to the above analysis data may be a bundle or set of analysis data generated based on the results of analyzing the above situation data. The pre-script may be analysis data obtained or generated based on the results of analyzing a specific event situation, such as an accident, a broken-down vehicle, construction work, traffic congestion, or road damage, that occurred on the moving route based on the above situation data. The analysis data may be video data related to the event. The analysis data may be full or summarized video data related to events related to traffic situations, such as accidents, broken-down vehicles, or traffic congestion. The analysis data may be full or summarized video data related to events related to road situations, such as construction work or road damage. The analysis data may be text information related to the event. The analysis data may be full or summarized text information related to events related to traffic situations, such as accidents, broken-down vehicles, or traffic congestion. The analysis data may be full or summarized text information related to events related to road situations, such as construction work or road damage. The analysis data may be data (e.g., video or text information) processed from raw data at the request or need of a user. The above event video data may be unprocessed raw data (e.g., video data or text information).

[0118] The electronic device (100) may, in operations 1021 and 1025, generate and / or output a response result using analysis data regarding the movement path (operation 530). The response result may be, for example, information that guides the situation of the movement path in response to a predetermined question related to the movement path and / or route guidance. The electronic device (100) may output the generated response result as visual information through a display. The electronic device may output the generated response result as auditory information through a speaker. The electronic device may output visual information and auditory information according to the generated response result through a display or a speaker, respectively.

[0119] According to an example, the electronic device (100) may determine, in operation 1021, whether a traffic situation (or road situation) guidance request exists. If the traffic situation (or road situation) guidance request exists, the electronic device (100) may generate a prompt for analyzing the cause and / or current situation of a specific event that occurred in the movement route (or selected route) in operation 1023. The electronic device (100) may generate the prompt using, for example, path-related information about the movement route (or selected route) and / or analysis data stored in the form of a script. The prompt may be, for example, “Please provide summary information about an accident that occurred at point a.”

[0120] The electronic device (100), in operation 1025, may generate a response result that guides traffic and / or road conditions from an AI model in response to the prompt. The electronic device (100) may output the response result. The electronic device (100) may, for example, use analysis data stored in a script form to output event image data related to the event and / or text information about the event as the response result. The event image data may be 3D image data generated by reprocessing an image captured by at least one camera. The specific event may include traffic congestion, an accident, or a construction situation on the determined movement path. For example, if provision of summary information on traffic and / or road conditions on the movement path is requested by the prompt, the electronic device (100) may read out target analysis data from pre-stored analysis data and output it. For example, if a prompt is requested to provide analysis information on a congested section in text format, the electronic device (100) can read out analysis data on the congested section from pre-stored analysis data and output it.

[0121] For example, the electronic device (100) may generate a prompt requesting guidance on overall or summary information related to traffic conditions and / or road conditions along a moving route. In this case, the electronic device (100) may generate overall or summary information related to traffic conditions and / or road conditions along a moving route based on analysis data (or a pre-script) stored in a script format and provide the information to the driver or user. The overall or summary information may be image data and / or text information. The electronic device (100) may, for example, generate overall or summary information related to a specific event based on the pre-script and provide the information to the driver or user. The overall or summary information may be image data and / or text information. The traffic conditions, the road conditions, or the specific event may be the same as defined above.

[0122] According to one example, the electronic device (100) may generate a prompt requesting analysis regarding the cause and / or current situation of a specific event occurring on the movement path. In this case, the electronic device (100) may process image data included in the situation data in an AI model to generate event image data related to the specific event. The electronic device (100) may output the event image data together with text information regarding the specific event. The event image data may be three-dimensional image data generated by reprocessing an image captured by at least one camera. The specific event may include traffic congestion, an accident, or a construction situation on the determined movement path.

[0123] According to one example, the electronic device (100) may receive situation data in real time from a target server, and based on this, generate analysis information related to a movement path and provide it to a driver or a user. The electronic device (100) may, for example, generate full information or summary information related to traffic conditions and / or road conditions of a movement path based on the real-time situation data and provide the information to the driver or the user. The full information or summary information may be image data and / or text information. The electronic device (100) may, for example, generate full information or summary information related to a specific event based on the real-time situation data and provide the information to the driver or the user. The full information or summary information may be image data and / or text information. The traffic conditions, the road conditions, or the specific event may be the same as defined above.

[0124] FIG. 11A is an exemplary diagram of a user interface that summarizes and provides status information about an entire moving path in an electronic device (e.g., the electronic device (100) of FIG. 1) according to one embodiment, FIG. 11B is an exemplary diagram of a user interface that summarizes and provides status information about a congested section of a moving path in an electronic device (e.g., the electronic device (100) of FIG. 1) according to one embodiment, and FIG. 11C is an exemplary diagram of a user interface that summarizes and provides road condition information about a moving path in an electronic device (e.g., the electronic device (100) of FIG. 1) according to one embodiment.

[0125] Referring to FIG. 11a, a user (1110a) can activate the route guidance function and request route guidance. For example, the route guidance request may be triggered by the user (1110a) saying, "Guide me to xxx" (1130b). Here, "xxx" may correspond to a destination.

[0126] The electronic device (100) with the above-mentioned route guidance function activated, upon receiving a request from the user (1110a), may determine a travel route from a starting point to a destination. For example, the electronic device (100) may suggest one or more candidate routes for arriving at a destination. The electronic device (100) may select one of the proposed one or more candidate routes as a travel route. The electronic device (100) may output a route guidance screen (1121a) through a display (1120a) based on the travel route. The route guidance screen (1121a) may include a starting point (1123a), a destination (1125a), and a travel route connecting the starting point (1123a) and the destination (1125a). For example, the route guidance screen (1121a) may include an event display (1127a) that occurred on the travel route. The above event indication (1127a) may indicate the occurrence of an event that may affect traffic conditions and / or road conditions, such as, for example, a traffic jam or an accident.

[0127] The electronic device (100) may, in response to the user's request, provide summary information (1140a) regarding traffic conditions and / or road conditions in relation to the route guidance screen (1121a) being output through the display (1120a). For example, the electronic device (100) may output summary information (1140a) related to an event that occurred on the travel route as visual information and / or auditory information. For example, the electronic device (100) may output summary information (1140a) for route guidance as an audio signal, such as, "There is severe traffic congestion in section A of the selected route. It occurred due to a triple-pileup accident on a four-lane road. The section has been congested for one hour. There is a traffic delay in section B due to road construction."

[0128] Referring to FIG. 11b, a user (1110b) may request detailed information regarding a specific event (1130b) while a route guidance screen (1121b) is being displayed on a display (1120b). The route guidance screen (1121b) may include, for example, a starting point (1123b), a destination (1125b), and a travel route connecting the starting point (1123b) and the destination (1125b). As an example, the route guidance screen (1121b) may include an event indication (1127b) that occurred along the travel route. The event indication (1127b) may indicate, for example, the occurrence of an event corresponding to a traffic congestion situation. As an example, the detailed information guidance request may be triggered by the user (1110b) saying, “Tell me more about the traffic congestion situation” (1130b).

[0129] Upon receiving a request from the user (1110b), the electronic device (100) may analyze the cause and / or current situation of a traffic congestion along the route based on a stored pre-script, and provide detailed information on the traffic congestion situation based on the analysis results. The stored pre-script analyzes situation data regarding the route received from the server, and stores the analysis data based on the analysis in the form of a script.

[0130] For example, the detailed information may include visual and / or auditory information (1140b) that provides information on the cause and / or current status of the traffic congestion. For example, the electronic device (100) may output detailed information (1140b) for route guidance as an audio signal, such as, "There is severe traffic congestion in Section A. Analysis of the cause of the congestion indicates that a triple-car pileup occurred on a four-lane road. The section has been congested for one hour, and it will take approximately five minutes from the current location to reach the congested section."

[0131] For example, the detailed information may include image data (1129b) related to the cause of a traffic jam. The image data (1129b) may be image data generated by reprocessing image data collected from a traffic jam that occurred along a moving path in an AI model to facilitate identification of the cause of the situation and / or the current situation. The image data (1129b) may be an image of an accident that caused the traffic jam.

[0132] The reprocessed image (1129b) may be displayed, for example, by dividing the display area of ​​the display (1120b) and together with the route guidance screen (1121b). The reprocessed image (1129b) may be displayed, for example, through a pop-up window in the display area of ​​the display (1120b) where the route guidance screen (1121b) is being displayed.

[0133] For example, the reprocessed video (1129b) may be generated based on video captured between the time a traffic jam occurs and any point after the traffic jam occurs, through interaction with the user (1110b). In this case, the user (1110b) may utilize playback-related controls, such as selecting a desired section to play, pausing video playback, or adjusting the video playback speed.

[0134] Referring to FIG. 11c, the electronic device (100) can display a route guidance screen (1121c) on the display (1120c). In the event of a special event, such as a multiple collision, the amount of situational data regarding the route to be guided may be excessive, resulting in a large amount of detailed information (1140c-1). Thus, the large amount of detailed information may be difficult to convey to the user.

[0135] The electronic device (100) may, when the amount of information to be provided is excessive, reduce the amount of information by analyzing and summarizing it using an AI model (e.g., LLM (250) of FIG. 2). For example, the electronic device (100) may output summary information (1140c-2) for route guidance as an audio signal, such as, “The road is congested due to a 13-car pileup in section xyz, and there is congestion due to road damage in section D. There are 120 other roads with special conditions, and some sections are congested.”

[0136] According to one example, an electronic device may include a communication circuit. The electronic device may include a memory including one or more storage media for storing instructions. The electronic device may include at least one processor including a processing circuit. When the instructions are individually or collectively executed by the at least one processor, the instructions may cause the electronic device to perform at least one operation. The at least one operation may include determining a movement path based on destination information. The at least one operation may include obtaining contextual data regarding the determined movement path from one or more servers connected to a network via the communication circuit. The contextual data may include image data captured at at least one specific point along the determined movement path. The at least one operation may include analyzing the contextual data in an artificial intelligence (AI) model to generate summary information regarding the determined movement path. The at least one operation may include displaying the generated summary information on a route guidance screen for the determined movement path.

[0137] For example, the image data may be image data captured by one or more cameras installed at the at least one specific point.

[0138] For example, the image data may be image data captured by a camera installed on another vehicle on a road section including at least one specific point.

[0139] In one example, a road section including at least one specific point may be a congested section in the determined travel route.

[0140] According to an example, the at least one operation may include an operation of determining a target time interval by considering an expected time required to the at least one specific point, and an operation of requesting a video or audio content of a length corresponding to the determined target time interval from the server.

[0141] In one example, the at least one operation may include an operation of storing the generated summary information in a script form, and an operation of generating summary information about traffic and / or road conditions throughout the determined movement path based on the summary information stored in the script form.

[0142] In one example, the at least one operation may include generating a prompt to analyze the cause and / or current situation of a specific event that occurred on the determined movement path, processing the image data in the AI ​​model in response to the prompt to generate event image data related to the specific event, and outputting the event image data together with text information about the specific event. The specific event may include traffic congestion, an accident, or a construction situation on the determined movement path.

[0143] According to one example, a method of operating an electronic device may be provided. The method may include an operation of determining a movement path of a vehicle based on destination information. The method may include an operation of determining a movement path based on the destination information. The method may include an operation of obtaining situational data regarding the determined movement path from one or more servers connected to a network. The situational data may include image data captured at at least one specific point of the determined movement path. The method may include an operation of analyzing the situational data in an artificial intelligence (AI) model to generate summary information regarding the determined movement path. The method may include an operation of displaying the generated summary information on a route guidance screen for the determined movement path.

[0144] For example, the image data may be image data captured by one or more cameras installed at the at least one specific point.

[0145] For example, the image data may be image data captured by a camera installed on another vehicle in a road section including at least one specific point. The road section including at least one specific point may be a congested section in the determined travel route.

[0146] In one example, the method may include determining a target time interval by considering the expected time required to reach at least one specific point. The method may include requesting a video or audio content of a length corresponding to the determined target time interval from the server.

[0147] For example, the operation of generating the summary information may include an operation of storing the generated summary information in a script format. The operation of generating the summary information may include an operation of generating summary information regarding traffic and / or road conditions throughout the determined travel route based on the summary information stored in the script format.

[0148] In one example, the method may include generating a prompt for analyzing the cause and / or current situation of a specific event occurring on the determined movement path. The method may include processing the image data in the AI ​​model in response to the prompt to generate event image data related to the specific event. The method may include outputting the event image data together with text information regarding the specific event. The specific event may include traffic congestion, an accident, or a construction situation on the determined movement path.

[0149] According to one example, a storage medium storing computer-readable instructions may be provided. The instructions, when executed by at least a portion of at least one processor of an electronic device, may cause the electronic device to perform at least one operation. The at least one operation may include determining a movement route based on destination information. The at least one operation may include obtaining context data regarding the determined movement route from one or more servers connected to a network via the communication circuit. The context data may include image data captured at at least one specific point of the determined movement route. The at least one operation may include analyzing the context data in an artificial intelligence (AI) model to generate summary information regarding the determined movement route. The at least one operation may include displaying the generated summary information on a route guidance screen for the determined movement route.

[0150] For example, the image data may be image data captured by one or more cameras installed at the at least one specific point.

[0151] For example, the image data may be image data captured by a camera installed on another vehicle on a road section including at least one specific point.

[0152] In one example, a road section including at least one specific point may be a congested section in the determined travel route.

[0153] According to an example, the at least one operation may include an operation of determining a target time interval by considering an expected time required to the at least one specific point, and an operation of requesting a video or audio content of a length corresponding to the determined target time interval from the server.

[0154] In one example, the at least one operation may include an operation of storing the generated summary information in a script form, and an operation of generating summary information about traffic and / or road conditions throughout the determined movement path based on the summary information stored in the script form.

[0155] In one example, the at least one operation may include generating a prompt to analyze the cause and / or current situation of a specific event that occurred on the determined movement path, processing the image data in the AI ​​model in response to the prompt to generate event image data related to the specific event, and outputting the event image data together with text information about the specific event. The specific event may include traffic congestion, an accident, or a construction situation on the determined movement path.

[0156] It should be understood that the embodiments of this document and the terminology used herein are not intended to limit the technical features described in this document to a specific embodiment, but include various modifications, equivalents, or substitutes of the embodiment. In connection with the description of the drawings, similar reference numerals may be used for similar or related components. The singular form of a noun corresponding to an item may include one or more of the item, unless the context clearly indicates otherwise. In this document, each of the phrases "A or B", "at least one of A and B", "at least one of A or B", "A, B, or C", "at least one of A, B, and C", and "at least one of A, B, or C" can include any one of the items listed together in the corresponding phrase among those phrases, or all possible combinations thereof. Terms such as "first," "second," or "first" or "second" may be used merely to distinguish one component from another, and do not limit the components in any other respect (e.g., importance or order). When a component (e.g., a first component) is referred to as "coupled" or "connected" to another (e.g., a second component), with or without the terms "functionally" or "communicatively," it means that the component can be connected to the other component directly (e.g., wired), wirelessly, or through a third component.

[0157] The term "module" used in one embodiment of this document may include a unit implemented in hardware, software, or firmware, and may be used interchangeably with terms such as logic, logic block, component, or circuit. A module may be an integral component, or a minimum unit or part of such a component that performs one or more functions. For example, according to one embodiment, a module may be implemented in the form of an application-specific integrated circuit (ASIC).

[0158] An embodiment of the present document may be implemented as software including one or more instructions stored in a storage medium (e.g., memory (230)) readable by a machine (e.g., electronic device (100)). For example, a processor (e.g., processor (210)) of the machine (e.g., electronic device (100)) may call at least one instruction among the one or more instructions stored from the storage medium and execute it. This enables the machine to operate to perform at least one function according to the at least one called instruction. The one or more instructions may include code generated by a compiler or code executable by an interpreter. The machine-readable storage medium may be provided in the form of a non-transitory storage medium. Here, 'non-transitory' simply means that the storage medium is a tangible device and does not contain signals (e.g., electromagnetic waves), and the term does not distinguish between cases where data is stored semi-permanently or temporarily on the storage medium.

[0159] According to one embodiment, the method according to one embodiment disclosed in the present document may be provided as a computer program product. The computer program product may be traded as a product between a seller and a buyer. The computer program product may be distributed in the form of a machine-readable storage medium (e.g., compact disc read-only memory (CD-ROM)), or may be distributed online (e.g., downloaded or uploaded) via an application store (e.g., Play Store™) or directly between two user devices (e.g., smart phones). In the case of online distribution, at least a portion of the computer program product may be temporarily stored or temporarily generated in a machine-readable storage medium, such as the memory of a manufacturer's server, an application store's server, or an intermediary server.

[0160] According to one embodiment, each component (e.g., a module or a program) of the above-described components may include one or more entities, and some of the entities may be separated and placed in other components. According to one embodiment, one or more components or operations of the aforementioned components may be omitted, or one or more other components or operations may be added. Alternatively or additionally, a plurality of components (e.g., a module or a program) may be integrated into a single component. In such a case, the integrated component may perform one or more functions of each of the plurality of components identically or similarly to those performed by the corresponding component among the plurality of components prior to the integration. According to one embodiment, the operations performed by a module, program, or other component may be executed sequentially, in parallel, iteratively, or heuristically, or one or more of the operations may be executed in a different order, omitted, or one or more other operations may be added.

Claims

1. In an electronic device (100), Communication circuit (240); A memory (230) including one or more storage media for storing instructions; and At least one processor (210) comprising a processing circuit, Here, when the above instructions are individually or collectively executed by at least one processor (210), Determine the route based on destination information, Obtaining situation data regarding the determined movement path from one or more servers connected to the network through the communication circuit (240), wherein the situation data includes image data captured at at least one specific point of the determined movement path, The artificial intelligence (AI) model analyzes the acquired situation data to generate summary information about the determined movement path. An electronic device (100) that operates to display the above-mentioned generated summary information on a route guidance screen for the above-mentioned determined movement route.

2. In paragraph 1, The above image data is image data captured by one or more cameras (821, 823, 825) installed at the at least one specific point and / or image data captured by a camera installed on a vehicle (841, 843, 845, 847, 849) in a road section including the at least one specific point. Here, the road section including at least one specific point is an electronic device (100) that is a congested section in the determined travel route.

3. In paragraph 1 or 2, When the above instructions are executed individually or collectively by at least one processor (210), Determine the target time interval by considering the expected time required to at least one specific point above, An electronic device (100) that operates to request video or audio content of a length corresponding to the target time period determined above from the server.

4. In any one of paragraphs 1 to 3, When the above instructions are executed individually or collectively by at least one processor (210), Save the summary information generated above in script form, An electronic device (100) that operates to generate summary information about traffic and / or road conditions throughout the determined movement route based on summary information stored in the form of the above script.

5. In any one of paragraphs 1 to 4, When the above instructions are executed individually or collectively by at least one processor (210), Generate prompts to analyze the cause and / or current situation of a specific event that occurred on the determined movement path, In response to the above prompt, the AI ​​model processes the image data to generate event image data related to the specific event, It operates to output the event video data generated above together with text information about the specific event. Here, the specific event includes a traffic jam, an accident, or a construction situation on the determined movement path, the electronic device (100).

6. In the operating method of the electronic device (100), Action (510) of determining a movement path based on destination information; An operation (520) of obtaining situation data regarding the determined movement path from one or more servers connected to the network, wherein the situation data includes image data captured at at least one specific point of the determined movement path; An operation (530) of analyzing the above situation data in an artificial intelligence (AI) model to generate summary information about the determined movement path; and A method comprising an action (530) of displaying the generated summary information on a route guidance screen for the determined movement route.

7. In paragraph 6, The above image data is image data captured by one or more cameras (821, 823, 825) installed at the at least one specific point and / or image data captured by a camera installed on a vehicle (841, 843, 845, 847, 849) in a road section including the at least one specific point. A method wherein a road section including at least one specific point is a congested section in the determined travel route.

8. In paragraph 6 or 7, An operation of determining a target time interval by considering the expected time required to at least one specific point; and A method comprising an action of requesting a video or audio content of a length corresponding to the target time period determined above to a corresponding server.

9. In any one of paragraphs 6 to 8, The action of generating the above summary information is: An action to save the above-mentioned generated summary information in script form; and A method comprising an action of generating summary information about traffic and / or road conditions throughout the determined movement route based on summary information stored in the form of the above script.

10. In any one of paragraphs 6 to 9, An action to generate a prompt for analyzing the cause and / or current situation of a specific event that occurred on the determined movement path; An operation of processing the image data in the AI ​​model in response to the above prompt to generate event image data related to the specific event; and Includes an action of outputting the above-generated event video data together with text information regarding the specific event, Here, the specific event includes a traffic jam, an accident, or a construction situation on the determined movement path.

11. In a storage medium that stores instructions that can be read by a computer, The above instructions, when executed by at least a part of at least one processor (210) included in the electronic device (100), cause the electronic device (100) to perform at least one operation, At least one of the above actions: Action (510) of determining a movement path based on destination information; An operation (520) of obtaining situation data regarding the determined movement path from one or more servers connected to the network, wherein the situation data includes image data captured at at least one specific point of the determined movement path; An operation (530) of analyzing the above situation data in an artificial intelligence (AI) model to generate summary information about the determined movement path; and A storage medium including an operation (530) of displaying the generated summary information on a route guidance screen for the determined movement route.

12. In paragraph 11, The above image data is image data captured by one or more cameras (821, 823, 825) installed at the at least one specific point and / or image data captured by a camera installed on a vehicle (841, 843, 845, 847, 849) in a road section including the at least one specific point. Here, a storage medium in which a road section including at least one specific point is a congested section in the determined travel route.

13. In paragraph 11 or 12, At least one of the above actions, An operation of determining a target time interval by considering the expected time required to at least one specific point; and A storage medium including an action of requesting a video or audio content of a length corresponding to the target time period determined above to a corresponding server.

14. In any one of paragraphs 11 to 13, The action of generating the above summary information is: An action to save the above-mentioned generated summary information in script form; and A storage medium comprising an operation for generating summary information about traffic and / or road conditions throughout the determined movement route based on summary information stored in the form of the above script.

15. In any one of paragraphs 11 to 14, At least one of the above actions, An action to generate a prompt for analyzing the cause and / or current situation of a specific event that occurred on the determined movement path; An operation of processing the image data in the AI ​​model in response to the above prompt to generate event image data related to the specific event; and Includes an action of outputting the above-generated event video data together with text information regarding the specific event, Here, the storage medium, wherein the specific event includes a traffic jam, an accident, or a construction situation on the determined movement path.

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