A method for building a complex exhibition, promotion, and education space that combines space and content

Abstract

The present invention relates to a technology for constructing an interactive experience space that fuses digital content with physical space. More specifically, regarding a specific space intended for exhibition, promotion, or education, the invention relates to a method and system for constructing a complex space that provides visitors with a high sense of immersion and a personalized experience and maximizes the efficiency of space operation by comprehensively collecting and analyzing three-dimensional spatial information, real-time changing visitor behavior information, and surrounding environment information, and dynamically generating and transforming simulation content based on virtual reality (VR) or augmented reality (AR) based on the analysis results.

Description

Technology Field

[0001] The present invention relates to a technology for constructing an interactive experience space that fuses digital content with physical space. More specifically, regarding a specific space intended for exhibition, promotion, or education, the invention relates to a method and system for constructing a complex space that provides visitors with a high sense of immersion and a personalized experience and maximizes the efficiency of space operation by comprehensively collecting and analyzing three-dimensional spatial information, real-time changing visitor behavior information, and surrounding environment information, and dynamically generating and transforming simulation content based on virtual reality (VR) or augmented reality (AR) based on the analysis results. Background Technology

[0002] Recently, various exhibition spaces, such as museums, art galleries, and corporate PR centers, are actively utilizing digital media to stimulate visitor interest and enhance the effectiveness of information delivery.

[0003] Conventional technology primarily utilized methods such as repeatedly playing pre-produced high-definition videos on large screens or projectors, or outputting content in a fixed sequence when a visitor's approach was detected by sensors installed at specific points. While this approach may be useful for conveying static information, it had limitations in that it could not actively respond to individual visitors' interests or viewing patterns because it unilaterally provided the same content to all viewers. Furthermore, since it did not consider real-time environmental changes such as the number or density of visitors, problems frequently occurred where content was obscured by other visitors or failed to be properly delivered when the space became crowded.

[0004] To overcome this, some technologies have provided supplementary information via smart devices through augmented reality (AR) applications or offered fully immersive experiences through virtual reality (VR) headsets. However, these technologies were limited to relying on the audience's personal devices or providing virtual spaces disconnected from the physical environment, demonstrating clear limitations in forming a collective experience by organically interacting with the environment of the physical space itself where multiple visitors gather.

[0005] In conclusion, conventional technologies have failed to provide an integrated solution that dynamically optimizes the content, format, and presentation method of content by comprehensively considering two key variables: real-time changing visitor behavior and the physical environment. The problem to be solved

[0006] The present invention was devised to solve the problems of the prior art as described above, and aims to solve the following technical problems.

[0007] It provides an intelligent content delivery method that moves away from one-way information delivery and objectively determines the audience's 'immersion' by analyzing behavioral information such as gaze, interaction, and location within the space in real time, and dynamically adjusts the pace of narrative development or the depth of content based on the results.

[0008] The goal is to overcome the physical limitations of actual exhibition environments where large crowds gather. Specifically, it minimizes the failure rate of content delivery in any congested situation by monitoring the number and density of visitors in real time to adjust the system's computational load, and by predicting potential future visual obstructions through the analysis of past movement patterns to preemptively position experience delivery units, such as mobile projectors, in optimal locations.

[0009] The goal is to maximize the stability and operational efficiency of the system. By automatically adjusting graphic precision based on the number of visitors or the degree of visual obstruction, it reduces unnecessary energy consumption and prevents system overload, thereby ensuring stable operation.

[0010] The present invention provides a method for constructing a complex space based on a new paradigm, where all components—from data collection, analysis, and decision-making to final implementation—are organically interconnected rather than operating independently, allowing visitors, the space, and the content to interact in real-time as a single integrated system.

[0011] The problems of the present invention are not limited to those mentioned above, and other problems not mentioned will be clearly understood by those skilled in the art from the description below. means of solving the problem

[0013] A method for constructing a complex exhibition space combining space and content, performed in a system comprising a data collection unit, a data analysis module, a narrative composition module, a simulation generation module, and an experience provision unit according to an embodiment of the present invention for solving the above problem,

[0014] (a) A step in which the data collection unit collects raw data including the behavior and physical environment of visitors within the experience space in real time;

[0015] (b) A step in which the data analysis module analyzes the collected raw data to generate feedback information indicating the experience state of the visitor and the environmental state of the space;

[0016] (c) A step in which the narrative configuration module generates control parameters that determine the narrative development method and the simulation representation method based on the generated feedback information;

[0017] (d) a step in which the simulation generation module applies the generated control parameters to dynamically generate an experience simulation to be provided to the spectator; and

[0018] (e) A step in which the experience providing unit provides the generated experience simulation to the visitor;

[0019] Includes,

[0020] The above step (a) is,

[0021] The data acquisition unit, comprising a 3D depth camera, an RGB camera, and a microphone, and having a central timestamp generator inside,

[0022] Collecting point cloud data representing the 3D position of an object from the 3D depth camera, image data for spectator identification from the RGB camera, and acoustic data representing the noise level of the space from the microphone, respectively;

[0023] It is characterized by generating a raw data stream with temporal consistency between heterogeneous data by assigning synchronized time information to all collected data packets through the central timestamp generator mentioned above.

[0024] In step (c) above, when the narrative configuration module generates control parameters that determine the variable precision of the simulation,

[0025] The above data analysis module calculates the number of valid visitors and the average visual obstruction rate of the space;

[0026] The above narrative configuration module determines a basic precision level of 'high', 'medium', or 'low' by comparing the number of valid visitors with a preset first visitor threshold and a second visitor threshold greater than the first visitor threshold; and

[0027] If the above average field of view obstruction rate exceeds a preset obstruction threshold rate, a step of determining the final variable precision by lowering the above determined basic precision level by one step;

[0028] Includes more,

[0029] In step (d) above, the simulation generation module is characterized by generating the experience simulation by adjusting the rendering resolution and graphic effects according to the final variable precision.

[0030] In the above step (b), when the data analysis module generates feedback information for determining the level of experience immersion of the visitors,

[0031] A step of calculating three judgment criteria including weighted average gaze holding time, converted interaction frequency, and ambient noise level;

[0032] A step of determining one of the basic immersion grades of 'High', 'Medium', and 'Low' by determining whether the weighted average gaze duration and the converted interaction frequency each exceed their respective thresholds (AND condition) or only one of them (XOR condition); and

[0033] A step of determining the final immersion level by lowering the determined basic immersion level by one step when the above ambient noise level exceeds a preset noise threshold;

[0034] Includes more,

[0035] The above weighted average gaze time is,

[0036] Based on visitor eye-tracking data collected through an infrared-based camera, it is calculated by assigning weights according to the preset information density or importance of the narrative element where the gaze rests;

[0037] The above reduced interaction frequency is,

[0038] It is characterized by summing up the results by applying predefined differential conversion values ​​based on the difficulty or time required for each type of interaction, according to the interaction event logs performed by the visitor.

[0039] In step (d) above, the simulation generation module generates a device-independent standard scene description format by applying control parameters and transmits it to the experience providing unit;

[0040] In step (e) above, the experience providing unit interprets the received standard scene technology format through a platform-specific renderer mounted internally to finally implement and provide the experience simulation in a form optimized for its own hardware; and

[0041] In step (b) above, the data analysis module is functionally separated into a 'real-time analysis engine' that processes real-time data streams and a 'batch analysis engine' that processes historical log data stored in a database, and operates to prevent heavy analysis work from affecting the generation of real-time feedback information;

[0042] It may include more. Effects of the invention

[0044] The present invention, for solving the above-mentioned problems, provides the following significant effects.

[0045] It is possible to maximize the experience satisfaction and immersion of visitors. The present invention analyzes visitors' behavior in real time to determine their level of interest and immersion, and accordingly adjusts the pace of the story's progression or provides personalized information. By enabling visitors to move beyond being passive observers and become active participants who influence the flow of the story, this provides a high level of immersion and satisfaction incomparable to conventional technology.

[0046] The efficiency and clarity of content delivery can be dramatically improved. This invention proactively avoids problems such as visual obstruction by comprehensively analyzing the physical environment, such as the number of visitors, density, and expected movement paths. By automatically positioning movable units to optimal locations and adjusting graphic representations according to congestion levels, it ensures that the intended design is clearly conveyed to visitors without distortion under any circumstances.

[0047] The stability and economic efficiency of system operations can be enhanced. Variable precision control logic, which dynamically adjusts the system's computational load according to the number of visitors, prevents unnecessary high-spec rendering, thereby preventing system overload and crashes. This ensures stable operation while simultaneously bringing about economic benefits by significantly reducing energy consumption.

[0048] Data-driven, scientific spatial operation and improvement become possible. Objective data accumulated during system operation, such as visitor movement patterns, average immersion levels, and interaction frequency, provides a basis for accurately identifying the popularity of specific content or issues with spatial design. Through this, operators can improve future content or efficiently redesign spaces based on data, rather than relying on intuition or surveys.

[0049] The effects according to the present invention are not limited to those exemplified above, and a wider variety of effects are included within the present invention. Brief explanation of the drawing

[0051] Figure 1 illustrates an overall relationship diagram according to the present invention. FIG. 2 is a flowchart showing the data and control flow between all components of a complex space construction system according to one embodiment of the present invention. FIG. 3 is a flowchart showing the detailed flow of a situation-adaptive precision control method corresponding to Process 1 of the present invention. FIG. 4 is a flowchart showing the detailed flow of a multi-factor-based immersion level determination method corresponding to process 2 of the present invention. FIG. 5 is a flowchart showing the detailed flow of a feedback-based narrative speed control method corresponding to process 3 of the present invention. FIG. 6 is a flowchart showing the detailed flow of a priority-based unit placement location selection method corresponding to process 4 of the present invention. Specific details for implementing the invention

[0052] Hereinafter, various embodiments are described in more detail with reference to the attached drawings. The embodiments described in this specification may be modified in various ways. Specific embodiments may be depicted in the drawings and described in detail in the detailed description. However, specific embodiments disclosed in the attached drawings are intended only to facilitate understanding of various embodiments. Accordingly, the technical concept is not limited by specific embodiments disclosed in the attached drawings, and it should be understood that it includes all equivalents or substitutions that fall within the spirit and scope of the invention.

[0053] Terms including ordinal numbers, such as first, second, etc., may be used to describe various components, but these components are not limited by the aforementioned terms. The aforementioned terms are used solely for the purpose of distinguishing one component from another.

[0054] The functions related to artificial intelligence according to the present disclosure are operated through a processor and memory. The processor may be composed of one or more processors. In this case, the one or more processors may be general-purpose processors such as CPUs, APs, and DSPs (Digital Signal Processors), graphics-dedicated processors such as GPUs and VPUs (Vision Processing Units), or artificial intelligence-dedicated processors such as NPUs. The one or more processors control the processing of input data according to predefined operation rules or artificial intelligence models stored in memory. Alternatively, if the one or more processors are artificial intelligence-dedicated processors, the artificial intelligence-dedicated processors may be designed with a hardware structure specialized for processing a specific artificial intelligence model.

[0055] The predefined rules of operation or artificial intelligence models are characterized by being created through learning. Here, being created through learning means that a basic artificial intelligence model is trained using a number of training data by a learning algorithm, thereby creating predefined rules of operation or artificial intelligence models configured to perform desired characteristics (or objectives). Such learning may be performed on the device itself where the artificial intelligence according to the present disclosure is executed, or it may be performed through a separate server and / or system. Examples of learning algorithms include supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning, but are not limited to the examples described above.

[0056] An artificial intelligence model can be composed of multiple neural network layers. Each of the multiple neural network layers has multiple nodes and weight values, and performs neural network operations through calculations between the results of previous layers and the multiple weights. The multiple weights possessed by the multiple neural network layers can be optimized based on the learning results of the artificial intelligence model. For example, multiple weights can be updated so that the loss value or cost value obtained by the artificial intelligence model during the learning process is reduced or minimized. Additionally, to minimize the loss value or cost value, multiple weights can be updated in a direction that minimizes the gradient associated with the loss value or cost value. Artificial neural networks may include deep neural networks (DNNs), such as Convolutional Neural Networks (CNNs), Deep Neural Networks (DNNs), Recurrent Neural Networks (RNNs), Restricted Boltzmann Machines (RBMs), Deep Belief Networks (DBNs), Bidirectional Recurrent Deep Neural Networks (BRDNNs), or Deep Q-Networks, but are not limited to the examples mentioned above.

[0057] A network is a network that serves as a transmission path for web pages; it may be a closed network such as a LAN (Local Area Network) or WAN (Wide Area Network), but it is desirable for it to be an open network such as the Internet. The Internet refers to a global open computer network structure that provides the TCP / IP protocol and various services existing at its upper layers, namely HTTP (HyperText Transfer Protocol), Telnet, FTP (File Transfer Protocol), DNS (Domain Name System), SMTP (Simple Mail Transfer Protocol), SNMP (Simple Network Management Protocol), NFS (Network File Service), and NIS (Network Information Service).

[0058] Terminals can be implemented in various forms. For example, the terminals described in this specification may include mobile terminals such as smartphones, tablet PCs, PDAs, portable multimedia players, and MP3 players, as well as fixed terminals such as smart TVs and desktop computers.

[0059] In this specification, terms such as “comprising” or “having” are intended to specify the existence of the features, numbers, steps, actions, components, parts, or combinations thereof described in the specification, and should be understood as not precluding the existence or addition of one or more other features, numbers, steps, actions, components, parts, or combinations thereof. When a component is described as being “connected” or “connected” to another component, it should be understood that it may be directly connected to or connected to that other component, or that there may be other components in between. On the other hand, when a component is described as being “directly connected” or “directly connected” to another component, it should be understood that there are no other components in between.

[0060] Meanwhile, a "module" or "part" for a component as used in this specification performs at least one function or operation. Furthermore, a "module" or "part" may perform a function or operation by hardware, software, or a combination of hardware and software. Additionally, a plurality of "modules" or a plurality of "parts," excluding a "module" or "part" that must be performed on specific hardware or on at least one processor, may be integrated into at least one module. A singular expression includes a plural expression unless the context clearly indicates otherwise.

[0061] In addition, power, power transmission, and control therefor for the following assembly configurations and embodiments, including "by control," follow conventional technology including terminals, applications, hardware control modules, etc., so they are omitted to avoid redundancy.

[0062] In addition, the operation embodiments and configurations described in a general manner without being explained in detail below follow the prior art and are omitted in order to focus on describing the purpose of the present invention and the resulting effects.

[0063] Furthermore, in describing the present invention, if it is determined that a detailed description of related known functions or configurations may unnecessarily obscure the essence of the invention, such detailed description is abbreviated or omitted.

[0064] The 'system for constructing a complex space for exhibition, promotion, and education combining space and content' for implementing the present invention digitizes physical space information and combines a narrative structure therewith to provide an interactive experience that responds in real time to changes in the behavior and environment of visitors. To this end, the system is configured to operate by organically including a data collection unit (100), a data processing module (200), a narrative composition module (300), a simulation generation module (400), an experience provision unit (500), and a data analysis module (600).

[0065] The system of the present invention adopts a centralized control architecture. Specifically, a narrative configuration module (300) that receives real-time feedback information processed from a data analysis module (600) performs the role of a central control tower. The narrative configuration module (300) exclusively handles and executes the core decision-making logic of the present invention, and transmits control parameters and specific operation commands based on the results to all other components (simulation generation module, experience provision unit, etc.). Through this, operational consistency of the entire system is ensured, and systematic decision-making regarding complex situations is enabled.

[0066] The data collection unit (100) is defined as a hardware assembly composed of multiple sensors that measure and collect raw data regarding the physical environment and visitor activities within the experience space in real time. The data collection unit (100) includes a 3D depth camera, a LiDAR sensor, a high-resolution RGB camera, and an omnidirectional microphone, and generates point cloud data representing the geometric structure of the space and the 3D location of objects, video data for visitor identification and eye tracking, and acoustic data for measuring the noise level of the space, respectively. In particular, the data collection unit (100) performs the function of ensuring temporal consistency between different types of data by assigning synchronized time information to data packets collected from all sensors through a central timestamp generator included internally. The data collection unit (100) transmits a raw data stream containing synchronized timestamps in real time to a data processing module (200) and a data analysis module (600) via a wired or wireless network.

[0067] In addition, the data collection unit (100) periodically corrects time information with a central server using a standard time synchronization technology such as the Network Time Protocol (NTP). Through this, sensor-specific clock errors that may occur during long-term operation are minimized, and precise time synchronization reliability in the order of milliseconds (ms) is maintained throughout the entire system.

[0068] The data processing module (200) is defined as a software module that processes raw data received from the data collection unit (100) to create and manage a structured digital space model that other modules of the system can reference. The data processing module (200) performs the function of creating a static 3D space model of fixed topographic features within the space before the system operation begins, and during system operation, projecting real-time location and shape data of dynamic objects, such as visitors or moving objects, onto the static model in an overlay manner to create final virtual environment data that is updated every frame. Here, the 'shape data' includes simplified geometric models, such as a 3D bounding box or an elliptical prism model, created based on the height and width information of each visitor. This is intended to effectively represent the physical occupied space while reducing the computational load of subsequent processing, such as calculating the visual obstruction rate. The module ensures temporal consistency of the data by grouping and processing only data within a set tolerance based on the timestamp of the received data into a single frame dataset. The data processing module (200) transmits the generated static 3D space model to the narrative configuration module (300) and the simulation generation module (400), and continuously transmits dynamic object data that is updated in real time to the simulation generation module (400).

[0069] The narrative configuration module (300) is a software module that performs core decision-making in the present invention and is defined to receive feedback from the data analysis module (600), determine the flow and expression method of the content, and transmit control commands to other related modules. To this end, the narrative configuration module (300) manages the entire narrative in the form of a finite state machine or a non-cyclic directed graph (DAG) composed of transition conditions between each scene and scenes. Through this data structure, the system can clearly ‘recognize’ and predict which zone the next scene to be activated belongs to and what narrative importance it has, based on the ID of the scene currently being played and transition conditions such as ‘acceleration’ determination. Instead of relying on a non-deterministic machine learning model, the narrative configuration module (300) operates based on an explicit set of logical rules, such as a ‘rule matrix’ and ‘hierarchical filtering’ as specifically described in the specification of the present invention, and performs the function of ensuring deterministic reproducibility that always outputs the same result for the same input conditions. The above narrative configuration module (300) receives state information analyzed from the data analysis module (600), transmits the determined narrative development speed parameter to the simulation generation module (400), and directly transmits the selected optimal placement location coordinates to the mobile experience providing unit (500).

[0070] The simulation generation module (400) is defined as a software module that synthesizes all types of data and control commands to generate visual and auditory content that each experience providing unit (500) will ultimately output. The simulation generation module (400) receives static / dynamic spatial data from the data processing module (200) and narrative control parameters from the narrative configuration module (300), synthesizes them, and performs the function of first generating data in a device-independent standard scene technology format. The standard format serves to standardize the content generation process for various hardware and maintain consistency, and transmits the generated standard scene technology format data to a specific experience providing unit (500) that will output the corresponding content.

[0071] The experience providing unit (500) is defined as a variety of hardware devices that implement a final audiovisual experience so that visitors can directly see, hear, and interact. The experience providing unit (500) includes a fixed projector, a mobile projector, an HMD, etc. Each unit is equipped with a 'platform-specific renderer' internally to perform the function of finally implementing and outputting a standard scene technology format received from the simulation generation module (400) in a form optimized for its own operating system and hardware. In addition, the experience providing unit (500) includes a standardized control interface for bidirectional communication with the central system, receives commands from the central system through an API that includes a predefined set of commands, and transmits data to the central system reporting its current status or visitor interaction input.

[0072] The data analysis module (600) is defined as a software module that analyzes raw data received from the data collection unit (100) to generate meaningful information necessary for real-time decision-making by the narrative composition module (300) or to store and process data for long-term analysis. The data analysis module (600) is functionally composed of two sub-modules, a 'real-time analysis engine' and a 'batch analysis engine,' to perform the function of preventing heavy analysis tasks from affecting the performance of the real-time feedback loop. The 'real-time analysis engine' directly processes real-time data streams in memory to immediately generate feedback data where latency is critical, and the 'batch analysis engine' periodically processes historical log data stored in a database to update the 'visitor traffic frequency heatmap' or generate long-term statistical reports. The data analysis module (600) receives raw data from the data collection unit (100), continuously transmits the generated real-time feedback data to the narrative composition module (300), and transmits updated heatmap data, etc., upon request from the narrative composition module (300).

[0073] The system of the present invention operates through the organic data flow and control process of the above components. Starting with the data collection unit (100) collecting raw data of the space in real time and transmitting it to the data analysis module (600), the 'real-time analysis engine' of the data analysis module (600) immediately analyzes it to generate meaningful feedback information and transmits it to the narrative configuration module (300). Based on the received feedback, the narrative configuration module (300) performs decision-making, such as narrative speed and unit placement location, according to the logic rules described in the specification of the present invention. In accordance with the above decision, the narrative configuration module (300) transmits control parameters to the simulation generation module (400) and directly transmits control commands to the corresponding experience provision unit (500), and the simulation generation module (400) generates standard scene description format data suitable for the current situation and transmits it to the experience provision unit (500). Finally, the experience providing unit (500) moves autonomously or outputs content according to the received commands and data, and all of this process is repeated at every moment to transmit commands so that the operation of the entire system changes organically according to the behavior of the audience or changes in the environment.

[0074] The complex space construction system according to the present invention includes a situation-adaptive precision control method to actively respond to the variable physical environment of the experience space and simultaneously achieve stable system performance and efficient resource usage. The precision control method provides technical means for dynamically determining the visual precision of an experience simulation by evaluating a plurality of predefined judgment criteria according to a stepwise and logical procedure. The precision control method utilizes two core judgment criteria as input data, and the first judgment criterion, the number of valid visitors, is defined as the total number of people located within the sphere of influence of the experience simulation provided by the system of the present invention, which is judged to have a direct impact on the computational load of the system. The sphere of influence is limited to the detection range of the data collection unit (100) or the valid space where content is projected, and is used as a core indicator that directly reflects the computational load of the system. The second judgment criterion, the average visual obstruction rate, is defined as the average ratio of the area where visual content projected from a projector or key digital objects are obscured by the bodies of other visitors due to the concentration of multiple visitors, and is used as a criterion for judging the validity of content delivery and whether resources are wasted.

[0075] The present invention determines the final precision by processing the two judgment criteria according to a sequential and hierarchical logical structure. The processing procedure first performs a first step of evaluating the overall load status of the system based on the 'number of valid visitors' to determine a basic precision level at which the system can operate stably. Subsequently, it sequentially performs a second step of evaluating the potential for resource waste based on the 'average visibility obstruction rate' and differentially lowering the basic precision level determined in the first step according to the degree in which the obstruction rate is compared with a plurality of threshold values. This second step procedure is based on the technical logic of 'securing stability first, then optimizing efficiency,' and operates in a manner that first satisfies the essential condition of stable system operation and then reduces unnecessary resource waste within that range, thereby executing commands that increase operational efficiency while preventing the interruption of the experience under any circumstances.

[0076] The above judgment criteria are obtained in an objective manner through a data collection unit (100) equipped in the system. A 3D depth camera or a plurality of wide-angle cameras included in the data collection unit (100) captures the experience space, and an object recognition algorithm is applied to the captured image data to detect objects with the shape of a human first, and the 3D location information and movement path of the detected objects are tracked to correct misrecognition. For example, at a specific time, the system detects 18 human-shaped objects in the space, but one of them is judged to be a fixed sculpture because it has not moved for more than 30 seconds, and transmits data confirming the number of valid visitors as '17 people'. The time threshold (e.g., 30 seconds) for misrecognition correction used in the present invention is set by statistically analyzing the average visitor movement path of the exhibition space and the minimum stay time at a specific point. For example, based on the statistical observation from the analysis of data collected during the initial stages of system operation that visitors exhibiting normal viewing patterns at any point show at least minimal, minute movements (turning head, changing posture, etc.) within 30 seconds, this serves as an objective criterion to determine that an object maintaining a perfectly stationary state beyond this time is highly likely to be a non-human object (sculpture). Additionally, the system identifies the projector's position, projection angle, and the 3D positional coordinates of each visitor in real time. Based on this, it generates a virtual light path connecting the projector's light source and the projection surface, and calculates the area obstructed by each visitor's body model along the path. For example, if the total projection area is 20㎡ and the total area obscured by 17 visitors is calculated to be 7㎡, the system transmits information confirming the average visual obstruction rate as '35%'.

[0077] At this time, in calculating the 'total occluded area,' the system generates 2D shadow polygons that each viewer's body model creates on the projection plane, and performs a union operation of all these shadow polygons. This method is intended to prevent overlapping areas from being counted redundantly when multiple viewers overlap and obstruct the view, and to accurately calculate the actual pure occluded area.

[0078] The variable precision finally determined through the above logical processing procedure is classified into three levels: 'High', 'Medium', and 'Low', and each level is converted into specific technical settings in the simulation generation module (400). The 'High' level sends a command to render at 4K resolution, fully enable real-time shadow and reflection effects, and use high-quality textures. The 'Medium' level sends a command to render at FHD resolution, disable real-time shadow effects, and disable some post-processing effects. The 'Low' level sends a command to render at HD resolution, use basic textures, and disable most real-time lighting and post-processing effects.

[0079] For example, a specific processing procedure for a situation where a space becomes crowded due to a group of visitors entering is performed step by step. First, the data collection unit (100) measures and transmits the number of valid visitors, '17 people', and the average view obstruction rate, '35%', as data at 2:05 PM. The simulation generation module (400) compares the received number of valid visitors, '17 people', with a pre-set first visitor threshold (10 people) and a second visitor threshold (50 people), and determines the basic precision level as 'medium'. Next, it compares the average view obstruction rate, '35%', with a pre-set first obstruction threshold (30%) and a second obstruction threshold (70%), and determines that the condition for a one-step downward adjustment is satisfied. Based on the above determination, a one-step downward adjustment is performed from the 'medium' level determined in step 2, and the final variable precision is confirmed as 'low'. Finally, the simulation generation module (400) sends a command to perform rendering by lowering the resolution of the simulation to HD and disabling some graphic effects according to the determined 'low' level.

[0080] The control method includes measures to ensure reliability and respond to exceptional situations. To prevent the number of valid visitors from changing abnormally rapidly due to a temporary error in the data collection unit (100), the system applies a moving average filter. The time window of the filter is set between 5 and 10 seconds, taking into account the average visitor entry / exit pattern, so that short-term measurement errors are filtered out while responding to actual changes in the number of visitors without delay. Additionally, if data reception is interrupted for more than 5 seconds, the system automatically switches to a pre-set 'safe mode', and when data reception resumes, after confirming that stable data is continuously received for at least 10 seconds, the system releases the 'safe mode' and sends a command to start situation-adaptive precision control again.

[0081] The effects are clearly evident when comparing the fixed precision method of the prior art with the situation-adaptive precision control of the present invention. In a scenario with a small number of visitors, the prior art simply provides a high-quality experience, whereas the present invention automatically sets the level to 'high' to maximize visitor satisfaction. On the other hand, in a scenario where a large group of visitors enters, the prior art suffers from a problem where the frame rate drops sharply due to overload, whereas the present invention automatically sets the level to 'low' to maintain a stable frame rate and significantly improves energy efficiency by stopping unnecessary graphic calculations.

[0082] Since the judgment rules of the present invention are based on physical reality measurable through sensors, the judgment process is guaranteed to be objective. Furthermore, as the number and density of visitors in an exhibition space are constantly fluctuating, it is determined that the technical configuration of the present invention, which dynamically controls precision, is inevitably required to achieve stability, efficiency, and satisfaction in response to variable environments. By adopting the aforementioned judgment criteria and logical processing procedures, the present invention achieves specific technical effects, such as securing system stability, increasing resource efficiency, and providing a consistent user experience.

[0083] The definitions of terms mentioned in the present invention and the criteria for setting threshold values ​​are as follows. The number of valid visitors is the total number of people located within the sphere of influence of the experience simulation provided by the system of the present invention, and who are judged to have a direct impact on the computational load of the system. The average visual obstruction rate is an indicator that quantifies the degree to which physical obstruction caused by a large number of visitors hinders the visual delivery of content. Variable precision is the level of graphic quality of the simulation that changes dynamically according to the real-time load and efficiency judgment of the system. The above visitor threshold values ​​are set through load testing of the hardware of the experience providing unit (500) constituting the system of the present invention, and periodically detect changes in hardware performance through a self-diagnostic function during system operation and transmit commands to automatically correct them. The above obstruction threshold rate is set based on the standard area where key visual objects defined in the content planning stage must secure minimum visibility, and is applied as a standard to balance resource efficiency and content delivery effectiveness.

[0084] The reason for using multiple interference thresholds in the present invention is to perform differential control according to the severity of resource waste. Specifically, the first interference threshold (e.g., 30%) is set at a level where, as a result of user testing, serious problems begin to occur in the 'delivery of core meaning' of the content and the audience's understanding drops sharply. On the other hand, the second interference threshold (e.g., 70%) is set at a level where, beyond the delivery of meaning of the content, it becomes almost impossible to perceive the projected 'visual form' itself, making graphic calculations completely meaningless.

[0085] The complex space construction system according to the present invention includes a multi-factor-based immersion level determination method for objectively identifying the visitor's experience state and feeding this into a content provision strategy. The method provides technical means for determining the level of immersion of currently provided content as a quantitative grade by comprehensively analyzing visitor behavioral data and surrounding environment data. The immersion level determination method comprehensively utilizes three core judgment criteria. The first judgment criterion, weighted average gaze retention time, is defined as the average time calculated by assigning weights based on the information density or importance of the element to the time a visitor intentionally fixes their gaze on a specific narrative element and stays there. The second judgment criterion, converted interaction frequency, is defined as the frequency calculated by converting interactions performed by the visitor during a unit of time into differential values ​​based on the difficulty or time required for each type and summing them up. The third judgment criterion, ambient noise level, is defined as the average noise level around the visitor within the experience space measured in decibels, and is used as an indicator to quantify external environmental factors that hinder experience immersion.

[0086] The present invention determines the final immersion level by processing the three judgment criteria according to a logical procedure of "evaluating a combination of positive factors followed by correction based on negative factors." In Step 1, the system determines the basic immersion level as "High" if both positive factors exceed their respective thresholds (AND condition). Additionally, it executes a command to determine it as "Medium" if only one of the two factors exceeds the threshold (XOR condition), and to determine it as "Low" if neither factor satisfies the threshold. In Step 2, it evaluates whether the negative factor, "ambient noise level," exceeds the threshold that causes serious interference with immersion; if it does, it determines that the basic immersion level determined in Step 1 is likely overestimated compared to the actual level and executes a command to downwardly correct the final immersion level by one step. This procedure provides a technical basis for analyzing the causes of reduced immersion more clearly and making sophisticated judgments by separating and evaluating the viewer's internal will and external environment.

[0087] The above judgment criteria are converted into objective data through a data collection unit (100) and an analysis module. An infrared-based camera of the data collection unit (100) applies eye-tracking technology that tracks the direction of the viewer's face and the position of the pupil, and the system calculates a weighted average gaze retention time based on the pre-set importance of each narrative element. For example, if a viewer maintains their gaze on a core object (weight 1.5) for 4 seconds and on an auxiliary image (weight 1.0) for 6 seconds, data confirming the weighted average gaze retention time as '4.8 seconds' is transmitted. Additionally, the data analysis module (600) aggregates the event logs of a specific viewer in 1-minute increments, applying conversion values ​​for each type of interaction to sum them up. For example, if a viewer performs 2 simple touches (2 points) and 1 AR puzzle solution (3 points) during the past minute, the converted interaction frequency is confirmed as '5 points per minute' and transmitted. Multiple omnidirectional microphones installed within the experience space measure sound pressure in real time, and the system determines and transmits the ambient noise level around a specific visitor as '62dB'.

[0088] The immersion level finally determined through the above procedure and the cause of determination are utilized by other modules of the system. The narrative composition module (300) determines the optimal measures by referring to the received immersion level as well as the cause of the determination. For example, if the level is downgraded due to noise, it transmits a command to provide sound-related auxiliary means, and if the level becomes 'low' due to a low frequency of interaction, it transmits a command to provide differentiated feedback by presenting new interaction elements. Additionally, the data analysis module (600) statistically analyzes the average immersion level of a specific area or content within the space and stores it to be used as data for future content improvement and space design optimization.

[0089] For example, a specific processing procedure is performed step by step for a situation where the surroundings become noisy while a visitor is viewing an exhibit. First, the weighted average gaze holding time of '6.5 seconds', converted interaction frequency of '7 points per minute', and ambient noise level of '75 dB' are measured and transmitted as data for the visitor. The data analysis module (600) determines the basic immersion level as 'High' because the positive factors exceed both the pre-set first immersion threshold time (5 seconds) and the second immersion threshold frequency (5 points per minute) (AND condition). Subsequently, it is determined that the immersion level down-correction condition is satisfied because the ambient noise level of '75 dB' exceeds the pre-set noise threshold (70 dB). Based on the above determination, a one-step down-correction is performed from the 'High' level to determine the final immersion level as 'Medium'. Finally, the identified 'medium' grade and the cause being 'high noise' are transmitted to the narrative configuration module (300), and the system is instructed to perform customized measures, such as projecting additional guidelines on the floor to increase visual focus or increasing the volume of personalized sound guidance.

[0090] This includes measures to ensure the reliability of the logic and to respond to exceptional situations. The system uses an infrared-based camera as an auxiliary tool to minimize the degradation of the recognition rate of the eye-tracking technology. If the eye data loss rate of a specific viewer exceeds 50% for one minute, it concludes that judgment based on eye data is unreliable and switches to determining a provisional immersion level using an 'auxiliary logic' that utilizes only interaction frequency and head direction data. The above 'auxiliary logic' operates according to the following specific alternative judgment rules: (1) If the converted interaction frequency exceeds the second immersion threshold frequency, the final immersion level is determined as 'medium'. (2) If (1) is not applicable, but the viewer's head direction data is maintained toward a specific narrative element for a certain period of time (e.g., 10 seconds) or longer, this is considered 'potential interest' and the final immersion level is determined as 'medium'. (3) If neither of the above two conditions applies, the final immersion level is determined as 'low'. This auxiliary logic is designed to minimize false positives and make conservative judgments by not determining a 'High' rating based on incomplete data. Additionally, in sections of viewing-type content without interactive elements, it automatically adjusts the converted interaction frequency threshold to '0' to prevent the logic from operating abnormally.

[0091] When comparing the present invention with the prior art method based on dwell time, the prior art misidentifies visitors who stay distractedly for a long time as being "immersed," whereas the present invention accurately identifies them as having a "low" rating. Furthermore, while the prior art fails to recognize situations where concentration is hindered by noise, the present invention recognizes the problematic situation by down-correcting it to a "medium" rating and provides auxiliary means appropriate to the cause. Since the judgment rules of the present invention are calculated based on objective physical quantities measured by sensors and clear criteria defined in advance, there is no room for arbitrary interpretation. Additionally, it is determined that the technical configuration of the present invention, which comprehensively considers multifaceted aspects such as the depth of interest, active participation, and distracting factors, is inevitably required to reliably determine a person's internal state of "immersion." By adopting these components, the present invention achieves technical effects such as sophisticated identification of visitor status, advanced personalized response, and deep data-based operational optimization.

[0092] The definitions of terms mentioned in this invention and the criteria for setting threshold values ​​are as follows. Weighted average gaze retention time is a value calculated by reflecting the importance of each element to determine the duration of a visitor's visual interest in a specific content element, and serves as an indicator representing the 'quality' of passive attention. Converted interaction frequency is a value that scores the act of an visitor actively communicating with the system by reflecting the difficulty level of each type, and serves as an indicator representing the 'quality' of active participation. The above converted values ​​are objectively set in proportion to the 'average task completion time' of each interaction. For example, if user tests conducted during the system construction phase measure the average time required for 'simple touch' as ​​1 second and the average time required for 'AR puzzle solving' as 3 seconds, the system automatically assigns converted values ​​of 1 point and 3 points, respectively, based on the time ratio. Through this, the temporal and cognitive effort invested by the visitor in a specific interaction is quantitatively evaluated, and this is fairly reflected in the judgment of immersion. The immersion rating is the level of experiential immersion of the visitor ultimately determined through the multi-factor analysis of this invention. The aforementioned immersion thresholds are set by comprehensively considering the average length of the content provided in the exhibition space, information density, and the difficulty of the designed interactions, and are determined at a statistically significant level by analyzing the average behavioral patterns of a user test group. The aforementioned noise threshold is set based on the average background noise of a typical exhibition environment to a level that causes obvious interference with visitors' listening to voice guidance or perception of content sounds, and a command to correct it is transmitted based on statistical data and user feedback.

[0093] The complex space construction system according to the present invention includes a feedback-based narrative speed control method for simultaneously optimizing visitor experience satisfaction and space operation efficiency. The method synthesizes the psychological responses of individual visitors into collective indicators, quantitatively analyzes the physical flow of the entire space to generate real-time feedback, and thereby provides technical means to dynamically adjust the development speed of a story implemented as digital content. The speed control method utilizes two core judgment criteria of different natures as input data, and the first judgment criterion, the average immersion grade by zone, is defined as the average grade calculated by synthesizing the immersion grades of valid visitors located in each zone that operates independently within the experience space. This serves as a micro-indicator that avoids the "trap of averages" and precisely represents the psychological response of a group of visitors to the content of a specific zone, and is used as a standard to precisely enhance visitor satisfaction by adjusting the development speed of the content in that zone. The second judgment criterion, spatial congestion status, is defined as state information in which changes in spatial congestion are classified as 'rapid inflow,' 'balanced,' or 'rapid outflow' by comprehensively considering the trend of visitor inflow / outflow rates over a unit of time and the absolute state of the current total number of visitors. As a macroscopic indicator representing changes in physical flow and density within the experiential space, this serves as a standard to enhance operational efficiency by reflecting not only simple rates of change but also the current level of congestion, thereby preventing bottlenecks within the space and inducing smooth visitor circulation.

[0094] The specific logical priority for determining the aforementioned 'space congestion status' is as follows. As the first priority, it is determined whether the current total number of visitors exceeds the 'cautionary stage congestion.' If it does, the final status is immediately confirmed as 'rapid inflow' regardless of other conditions. As the second priority, the net increase in visitors per unit of time is calculated only if the first priority is not met. If this net increase exceeds the 'inflow threshold,' it is determined as 'rapid inflow'; if it exceeds the 'outflow threshold,' as 'rapid outflow'; and if it falls between these values, as 'balanced.' Through these priority rules, the current absolute risk state is always considered before the trend of change.

[0095] The present invention follows a matrix-based logic rule that determines the narrative development speed by combining the states of the two judgment criteria. The rule first performs a first step of determining the 'average immersion level by zone' and the 'space congestion status' in three stages each. At this time, if the current total number of visitors exceeds the 'cautionary stage congestion level,' it includes a correction step that determines the congestion status by forcibly assigning a weight equivalent to the 'fast inflow' state, regardless of the actual inflow / outflow rate. Subsequently, based on the combination of the states of the two criteria determined in the first step, it performs a second step of finally determining the narrative development speed of the corresponding zone as one of 'acceleration,' 'maintenance,' or 'deceleration' based on a pre-defined rule matrix. This matrix-based procedure aims to find the optimal balance between the two potentially conflicting goals of visitor satisfaction and operational efficiency. It provides specific technical criteria for making decisions regarding complex situations, such as minimizing adverse effects caused by abrupt changes by making a neutral decision to "maintain" when "high immersion" and "rapid influx" occur simultaneously, leading to a clash between opposing demands for visitor satisfaction and spatial congestion relief.

[0096] The above judgment criteria are calculated through objective data. The data analysis module (600) aggregates the immersion grade of individual visitors determined in process 2 in real time for each zone, but if the number of visitors in the zone is less than the preset minimum sample size, it performs an exception processing to prevent statistical distortion by not calculating the average grade and considering it as an 'intermediate' grade. For example, if there are 10 visitors in Zone A, and it is determined that there are 4 visitors (40%) with a 'high' grade, 5 visitors (50%) with an 'intermediate' grade, and 1 visitor (10%) with a 'low' grade, the system generates information determining the average immersion grade of Zone A as 'intermediate' because the proportion of 'high' grades (40%) does not exceed the 'high standard ratio' (e.g., 50%) and the proportion of 'low' grades (10%) does not exceed the 'low standard ratio' (e.g., 50%). This ratio-based determination method excludes the introduction of an arbitrary scoring system and more intuitively reflects the distribution of the group's state. Additionally, the data collection unit (100) counts the number of people entering and exiting over the past 5 minutes through the entrance and exit sensors of the experience space and determines the current total number of people. For example, if the current total number of people is less than the 'caution stage' and the net increase in people over the past 5 minutes exceeds a threshold of 10 people, data is transmitted to determine the space congestion state as 'rapid inflow'.

[0097] The narrative development speed finally determined through the above procedure is applied to the simulation in a specific manner by the narrative configuration module (300). When 'accelerate' is determined, a command is sent to shorten the length of the content currently being played to 1.2 times the speed or to skip additional explanation steps and quickly switch to the next core story. When 'maintain' is determined, a command is sent to play the content normally at a preset default speed. When 'decelerate' is determined, a command is sent to slow down the content playback speed to 0.8 times the speed or to provide additional information or interactive elements regarding the current scene to induce the audience to stay longer and explore.

[0098] For example, a specific processing procedure is performed step by step for a situation where immersion is high in a specific popular section but the space becomes increasingly crowded. First, the average immersion level of the area is determined to be 'high', and the space congestion status is determined to be 'fast inflow'. The narrative composition module (300) inputs the two states of 'high immersion' and 'fast inflow' into a rule matrix and determines the final speed to 'maintain' the current speed as is in order to balance the two goals. Based on this decision, the system continues to play the content of the area at the default speed and executes a command to maintain the current state until a significant change occurs in the audience flow or immersion.

[0099] It includes a safety mode to ensure the reliability of this logic and to respond to exceptional situations. If an emergency is detected where the total number of visitors in the space exceeds 90% of the safe capacity, the system forcibly sets the narrative development speed to 'maximum acceleration' regardless of the immersion level of all zones and sends a command to induce rapid crowd dispersion by projecting visual guidance toward the exit. The safety mode is automatically deactivated when the total number of visitors decreases to less than 80% of the safe capacity and remains stable for at least 5 minutes, and a command is executed to return to normal feedback-based speed control logic.

[0100] When comparing the prior art fixed-speed playback method with the present invention, in quiet spaces exhibiting high immersion, the prior art switches scenes regardless of the viewer's intent, whereas the present invention automatically determines 'deceleration' to maximize satisfaction. Conversely, in crowded spaces exhibiting high immersion, the prior art causes bottlenecks, whereas the present invention determines 'maintenance' or 'gradual acceleration' to find a balance between satisfaction and operational efficiency, thereby mitigating bottlenecks. The objectivity of the judgment rules of the present invention is guaranteed because results are derived by inputting objective data into an explicit rule matrix. Furthermore, it is determined that the technical configuration of the present invention, which receives real-time feedback on these two disparate elements and dynamically controls their interaction, is inevitably required to resolve the complex issue of psychological viewer satisfaction and the physical capacity of the space. By adopting these components, the present invention achieves technical effects such as maximized viewer satisfaction, improved operational efficiency and stability, and automated intelligent operation.

[0101] The definitions of terms mentioned in this invention and the criteria for setting threshold values ​​are as follows. The average immersion rating by zone is a comprehensive indicator representing the psychological response of visitors in a specific zone within the experience space. The spatial congestion status is a physical state indicator that comprehensively reflects the current density of the space and future change trends. The narrative development speed is the pace of the story progression implemented as digital content. The aforementioned average "immersion level" threshold is set based on statistical data collected through user testing, with the average score range where 80% or more of the test group expressed satisfaction set as the standard for a "high" grade. The aforementioned congestion-related thresholds are set through simulations that consider the physical size of the exhibition space, maximum capacity, and average viewing flow, enabling a preemptive response before problems occur. The aforementioned "cautionary level congestion" threshold (e.g., 75% of maximum capacity) is set by primarily complying with the appropriate number of people per unit area stipulated by relevant fire and safety regulations, and secondarily by considering the statistical density point where visitors begin to psychologically feel "crowded" based on user satisfaction survey results. This serves as an objective standard for the system to maintain a pleasant viewing environment while meeting legal safety standards. The minimum sample size is a criterion to ensure statistical reliability and is, in principle, set by considering the size of the space and general visitor density.

[0102] The complex space construction system according to the present invention includes a priority-based unit placement location selection method to maximize the utility of a mobile experience providing unit (500) and minimize the failure rate of content delivery. The method relates to a technical means for selecting, in real time, one optimal location that is most suitable for the ever-changing exhibition environment and the context of the content by applying multiple judgment criteria to multiple potential placement locations existing within the experience space. The location selection method utilizes four core judgment criteria to comprehensively evaluate the validity of the placement. The first judgment criterion, effective coverage area, is defined as an effective area where content can reach without being obstructed by fixed obstacles when a unit is placed at a specific candidate location, and is used as the most basic positive factor for evaluating the physical range of content delivery. The second judgment criterion, narrative importance, is defined as a relative importance grade assigned to each space area according to the narrative structure of the story during the content planning stage, and is used as a core positive factor for judging the qualitative value of the placement as a setting value for the system to technically implement the planner's creative intention. The third judgment criterion, the predicted visibility obstruction rate, is defined as the probability that the projection path will be obscured by moving visitors when content is projected from a specific candidate location, based on historical visitor movement pattern data that is automatically updated periodically. It is used as a key negative factor to predict and avoid potential dynamic obstacles that may occur in the future. The fourth judgment criterion, the adjacent unit interference rate, is defined as a risk grade determined based on a predefined 'inter-unit interference matrix' regarding the interaction characteristics between a specific candidate location and other units. It is used as a negative factor to ensure the overall stability of the system by comprehensively evaluating the possibility of complex interference between homogeneous and heterogeneous units. The aforementioned 'adjacent unit interference rate' is quantitatively determined based on the predefined 'inter-unit interference matrix'.The above matrix defines the interference coefficient for each unit combination, with unit types (projectors, speakers, lighting, etc.) serving as rows and columns. For example, a high interference coefficient is assigned between homogeneous units (projector-projector), a low interference coefficient between mutually complementary heterogeneous units (projector-speaker), and a high interference coefficient between interfering heterogeneous units (specific lighting-projector color distortion). The system calculates the final interference grade by considering the distance between candidate locations and other units, along with the values ​​in this matrix.

[0103] The present invention follows a clear and systematic logical procedure of 'hierarchical filtering and priority determination' to select one optimal location among multiple candidate locations. In the first step, the system selects valid candidate locations by first excluding locations that fail to secure a minimum content delivery range based on the 'effective coverage area'. In the second step, negative factors such as 'expected view obstruction rate' and 'adjacent unit interference' are evaluated on the candidate locations that passed the first step; if either of these two factors exceeds a pre-set risk threshold, the location is determined to have low placement stability and is further excluded. In the final third step, among the remaining candidate locations that passed up to the second step, the location with the highest 'narrative importance' is selected based on the first priority criterion. If there are multiple locations with the same first priority criterion, the location with the lowest 'expected view obstruction rate' among them is selected based on the second priority criterion. If there are multiple candidate locations with the same second priority criterion, the location with the largest 'effective coverage area' among them is selected based on the third priority criterion. If there are multiple final candidates that meet all three of the above priority conditions, the location closest to the current mobile unit is finally selected to minimize the energy and time required for movement. This multi-stage priority determination rule ensures that only one optimal location can be deterministically selected in any case.

[0104] The above judgment criteria are calculated using objective data. The system calculates the effective coverage area of ​​each candidate location in square meters, such as '15㎡', by referring to a pre-constructed 3D digital map of the space. Additionally, the data analysis module (600) periodically automatically updates the 'visitor traffic frequency heatmap' by reflecting the latest visitor location data continuously collected during system operation, and calculates the expected visibility obstruction rate of each candidate location as a probability value, such as '40%', based on this. Furthermore, the system generates data that determines the degree of interference between adjacent units of each candidate location as 'high' grade by referring to a pre-defined 'interference matrix between units'. The final placement location selected through the above procedure is transmitted to a mobile experience providing unit (500), and the unit moves to the designated location via an autonomous driving function to perform the mission of projecting content or transmitting sound, and executes a command to send a placement completion signal back to the central system.

[0105] For example, a specific processing procedure is performed step by step for a situation where a mobile projector needs to be relocated to express the climax of a story. First, the effective coverage area is evaluated, and candidate location B (8㎡), which is less than the minimum critical area (10㎡), is eliminated in the first stage. Risk factors are evaluated for the remaining effective candidates A and C, and candidate A, whose expected interference rate (40%) exceeds the critical rate (30%), is eliminated in the second stage. C, which remains as the only final candidate, is selected as the final placement location, and a command is sent to the mobile projector to move to the corresponding coordinates.

[0106] This includes measures to ensure the reliability of the logic and to respond to exceptional situations. If all candidate locations are eliminated in the second stage of filtering and no final candidates remain, the system determines the state as 'unavailable for placement' instead of taking the risk and forcing placement, and sends a command to automatically execute a pre-designed 'alternative narrative scenario' that conveys the core content of the current narrative using only fixed units, without presupposing the use of movable units. The aforementioned 'alternative narrative scenario' refers to a pre-designed sequence of reserve content that conveys a condensed version of the core content of the current narrative using only fixed units (e.g., wall screens, ceiling speakers) without presupposing the use of movable units. If there is no pre-defined alternative scenario for the current narrative, the system sends a warning notification of the 'unavailable for placement' state to the operator and prevents confusion among visitors by broadcasting only a minimal guidance message, such as 'Please move to the next area,' through the nearest fixed unit. When comparing the present invention with the prior art method of moving to the nearest empty space, in a situation where the central corridor is empty, the prior art fails to deliver content due to visitor traffic, whereas the present invention delivers stable content by avoiding that location based on the 'expected visual obstruction rate.' Furthermore, when the physical conditions of the two locations are similar, the prior art may select a location unrelated to the context, whereas the present invention maximizes the dramatic effect of the content by prioritizing 'narrative importance.'

[0107] The judgment rules of the present invention ensure objectivity by performing clear filtering and priority comparisons based on objective data, such as a 3D map of space, a statistical heatmap that is periodically updated, and predefined importance and interference matrices. Since the value of a mobile unit is determined by the quality of the decision regarding "where to move," the technical configuration of the present invention, which predicts the future through past data, considers the context of the content, and comprehensively determines the optimal location that achieves harmony within the entire system, is deemed to be inevitably required to maximize the utility of the mobile unit. By adopting these components, the present invention achieves technical effects such as maximizing the success rate of content delivery, enhancing experiential immersion, and ensuring system operational stability.

[0108] The definitions of terms mentioned in this invention and the criteria for setting thresholds are as follows. The effective coverage area is the size of the pure area where the unit's signal reaches, excluding fixed obstacles. The predicted visibility obstruction rate is the probability that content will be obscured by dynamic obstacles, predicted based on historical data that is periodically updated. Hierarchical filtering is a decision-making method that compresses targets by applying conditions stepwise to multiple candidate groups. The placement threshold area is set based on the physical distance and area required to guarantee the minimum resolution or minimum sound pressure of the content provided by the unit. The placement threshold rate is set by statistically analyzing the level of visibility obstruction at which serious problems begin to occur in conveying the meaning of the content through user testing. In principle, the interference risk distance and matrix are set based on the effective signal range and interference characteristics specified in the technical specifications of the unit being used.

[0109] Through a specific scenario in which the system of the present invention actually operates, we will explain in detail how each component and core process are organically linked. The present invention is implemented in an exhibition space with the theme of "Exploring Ancient Ruins" during the busy time of 2 PM on a weekend. The space is divided into "Zone 1: Temple Entrance" and "Zone 2: Central Altar," where the narrative importance is set to "core," and it is assumed that a mobile projector unit is in operation.

[0110] In the initial state, when about 20 visitors are staying in Zone 1 and the system is operating stably, a group of 30 visitors enter Zone 1 all at once, causing a change in the environment. Accordingly, the 3D depth camera and RGB camera of the data collection unit (100) immediately detect the increase in the number of people, and the omnidirectional microphone detects the increased noise. The unit assigns time information synchronized with all sensor data and transmits this raw data stream in real time to the data analysis module (600) and the data processing module (200).

[0111] The 'real-time analysis engine' of the data analysis module (600) immediately processes the received data. First, it calculates that the number of valid visitors in Zone 1 has surged to 50 and the average visibility obstruction rate is 45%. At the same time, it detects a pattern in which most visitors cannot focus on the content due to sudden congestion and noise, and determines the average immersion level of Zone 1 as 'low'. In addition, it analyzes the entrance / exit sensor data to determine the spatial congestion status as 'rapid inflow', and bundles all these analysis results into a single feedback package and transmits it to the narrative composition module (300).

[0112] The narrative configuration module (300) sequentially performs comprehensive decision-making according to the core logic of the present invention based on the received feedback package. First, by applying two states, 'low immersion' and 'fast inflow,' to the rule matrix, the narrative development speed of the first zone is determined to be 'accelerated' in order to quickly pass through the current boring section and guide the audience to the next zone. Based on the 'accelerated' decision, it recognizes that the flow of the story will soon move to the second zone, which is the 'core' of narrative importance, and decides to relocate the movable projector unit to the second zone. Subsequently, hierarchical filtering is performed on possible candidate locations within the second zone, and by referring to the latest heatmap managed by the 'placement analysis engine' of the data analysis module (600), the central passage is determined to have a high 'expected visual obstruction rate' and is excluded, and among the locations satisfying all conditions, the optimal placement location that best corresponds to the 'core' of narrative importance is finally selected at a specific coordinate.

[0113] Based on the above decision, the narrative configuration module (300) transmits the 'narrative speed = acceleration' parameter to the simulation generation module (400) and directly transmits a control command to move to the selected optimal position coordinates to the mobile projector unit. At the same time, the simulation generation module (400) determines the graphic precision to a 'low' level based on the 'number of valid viewers = 50' and 'average view obstruction rate = 45%' received from the data analysis module (600). Then, in accordance with the determined 'low' precision and 'acceleration' speed, it generates device-independent standard scene technology format data including the finishing video of the first zone and the core video of the second zone, and transmits this to the mobile projector unit.

[0114] Finally, the mobile projector unit receives commands and data from two other sources and performs tasks simultaneously. Upon receiving a movement command from the narrative configuration module (300), it stops projection in the first zone and begins autonomous driving toward a selected optimal location. It stores content data received from the simulation generation module (400) in an internal buffer and, upon arriving at the target location, reports a 'placement complete' signal to the central system. Upon receiving the 'placement complete' signal, the narrative configuration module (300) sends a specific execution command, 'Start projection of content ID-XXX,' back to the mobile projector unit. Subsequently, the 'platform-specific renderer' inside the unit interprets the received standard scene technical format data and executes a command to start projecting the core image of the second zone onto the wall in a form optimized for 'low' precision.

[0115] Subsequently, while visitors move to the second zone, the data collection unit (100) continuously detects the new environment and transmits data, and the system continuously repeats the process of analysis, decision-making, control, and implementation described above. If visitors in the second zone show high immersion, the system transmits commands to organically adapt to the changing environment, such as changing the narrative speed to 'decelerate' and increasing the graphic precision to 'high' when the space becomes less crowded again. In this way, the system of the present invention commands that each component and process interact organically with a clear role to implement an experience that is stable, efficient, and provides high satisfaction even in a complex and unpredictable real exhibition environment.

[0116] Although preferred embodiments of the present invention have been illustrated and described above, the present invention is not limited to the specific embodiments described above. Various modifications are possible by those skilled in the art without departing from the essence of the invention as claimed in the claims, and such modifications should not be understood individually from the technical spirit or perspective of the present invention. Explanation of the symbols

[0117] Data collection unit (100) Data processing module (200) Narrative composition module (300) Simulation generation module (400) Experience provision unit (500) Data analysis module (600)

Claims

Claim 1 A method for constructing a complex exhibition space combining space and content, performed in a system comprising a data collection unit, a data analysis module, a narrative construction module, a simulation generation module, and an experience provision unit, comprising: (a) a step in which the data collection unit collects raw data in real time including the behavior of visitors and the physical environment within the experience space; (b) a step in which the data analysis module analyzes the collected raw data to generate feedback information indicating the experience state of the visitors and the environmental state of the space; (c) a step in which the narrative construction module generates control parameters that determine the narrative development method and the simulation expression method based on the generated feedback information; (d) a step in which the simulation generation module applies the generated control parameters to dynamically generate an experience simulation to be provided to the visitors. A method for constructing a complex space for exhibition, promotion, and education combining space and content, comprising: (e) a step in which the experience providing unit provides the generated experience simulation to the visitor; wherein step (a) is characterized in that the data collection unit, which includes a 3D depth camera, an RGB camera, and a microphone and has a central timestamp generator inside, collects point cloud data representing the 3D position of an object from the 3D depth camera, image data for visitor identification from the RGB camera, and acoustic data representing the noise level of the space from the microphone, respectively; and generates a raw data stream in which temporal consistency between heterogeneous data is ensured by assigning time information synchronized to all collected data packets through the central timestamp generator; and in step (c), when the narrative configuration module generates control parameters determining the variable precision of the simulation, the data analysis module calculates the number of valid visitors in the space and the average visual obstruction rate.The narrative configuration module further comprises the step of determining a basic precision level among 'high', 'medium', and 'low' by comparing the number of valid viewers with a preset first viewer threshold and a second viewer threshold greater than the first viewer threshold; and the step of determining a final variable precision by lowering the determined basic precision level by one step if the average visual obstruction rate exceeds a preset obstruction threshold; wherein, in step (d), the simulation generation module generates the experience simulation by adjusting the rendering resolution and graphic effects according to the final variable precision; and in step (b), the data analysis module generates feedback information for determining the experience immersion level of the viewers, comprising the step of calculating three judgment criteria including weighted average gaze retention time, converted interaction frequency, and ambient noise level; and the step of determining a basic immersion level among 'high', 'medium', and 'low' by determining whether both the weighted average gaze retention time and the converted interaction frequency exceed their respective thresholds (AND condition) or only one of them exceeds their respective thresholds (XOR condition). The method for constructing a complex space for exhibition, promotion, and education combining space and content further comprises the step of determining a final immersion level by lowering the determined basic immersion level by one step when the ambient noise level exceeds a preset noise threshold; wherein the weighted average gaze retention time is calculated by assigning weights based on the viewer's gaze tracking data collected through an infrared-based camera, according to the preset information density or importance of the narrative element where the gaze rested; and wherein the converted interaction frequency is summed by applying a preset differential conversion value based on the difficulty or time required for each type of interaction, based on the interaction event logs performed by the viewer. Claim 2 delete Claim 3 delete Claim 4 delete Claim 5 delete Claim 6 A method for constructing a complex space for exhibition, promotion, and education combining space and content, further comprising: in step (d), the simulation generation module, by applying control parameters, generates a device-independent standard scene description format and transmits it to the experience providing unit; in step (e), the experience providing unit, by interpreting the received standard scene description format through a platform-specific renderer mounted internally, and finally implementing and providing the experience simulation in a form optimized for its own hardware; and in step (b), the data analysis module, by being functionally separated into a 'real-time analysis engine' that processes real-time data streams and a 'batch analysis engine' that processes historical log data stored in a database, and operating to prevent heavy analysis work from affecting the generation of real-time feedback information.

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