Dynamically Path-Changing Maze Attraction System and Theme Park RPG System

Abstract

By utilizing AI to dynamically change the maze's paths, this maze-type attraction system provides visitors with a constantly fresh experience, allowing them to enjoy a sense of adventure even while waiting. [Solution] The dynamic path-changing maze attraction system features an AI-controlled variable maze structure, visitor detection using sensors, and the ability to link with other attractions. It provides an immersive experience through smartphone connectivity, IoT wearables, AR / VR / holograms, and multi-sensory effects.

Description

[Background technology]

[0001] This invention relates to maze-type attractions in theme parks, amusement facilities, leisure facilities, etc., and more particularly to an attraction system that can dynamically change the maze's path using artificial intelligence (AI). More specifically, this invention belongs to the field of personalized adaptive entertainment systems, which integrates the latest technologies such as IoT (Internet of Things) sensor networks, machine learning algorithms, AR (augmented reality) / VR (virtual reality) technology, biometric information analysis, environmental control systems, and blockchain technology as next-generation entertainment technology, and optimizes the maze structure and performance content in real time according to the preferences, behavior patterns, and physiological state of each visitor. This system is an innovative attraction technology that fundamentally transforms conventional static attraction design and simultaneously achieves improved visitor satisfaction, operational efficiency, increased profitability, and reduced environmental impact. It also addresses social demands such as accessibility, multilingual and multicultural support, safety management, and privacy protection, aiming to build a sustainable and inclusive entertainment environment.

[0002] Conventionally, in theme parks and amusement facilities, various attractions have been provided to entertain visitors. Among them, maze-type attractions are popular among people of all ages and genders and are adopted by many facilities. The history of maze-type attractions is ancient. From the mythical labyrinth on the island of Crete in ancient Greece to modern theme parks, humans have felt a universal charm in the structure of mazes. Maze attractions in modern commercial facilities were formally introduced in theme parks in Europe and the United States after the 1960s and have become popular attractions in amusement parks across Japan since the 1980s. However, conventional maze-type attractions are mainly fixed structures composed of physical walls and hedges, and it has been difficult to make basic route changes once they are built. In addition, the individual response to the diverse needs (age, physical strength, hobbies, cultural background, etc.) of visitors is also limited, and it often remains at the setting of an average difficulty level for everyone. According to recent market research, 65% of theme park visitors are seeking a "customized experience tailored to individuals," and in particular, among the younger generation (18 - 34 years old), 78% attach importance to a personalized entertainment experience.

[0003] However, traditional maze-type attractions have a problem: once constructed, the routes are fixed, which can lead to a lack of novelty and monotony for repeat visitors. Furthermore, waiting times are often spent simply standing in line, resulting in wasted time. This problem of fixed routes has become a significant management challenge for theme park operations. Industry surveys show that the repeat visitor rate for maze-type attractions tends to drop to an average of 23% six months after the first visit, and further to 11% after one year. Additionally, traditional waiting systems result in average wait times of 45 to 90 minutes, significantly reducing visitor satisfaction during this time (satisfaction score of 3.2 out of 10). Moreover, fixed maze structures present numerous operational constraints, including difficulty in controlling crowd flow during peak hours, safety concerns due to excessive concentration in specific areas, inefficient cleaning and maintenance, and difficulty in adapting to seasonal events and other occasions. Furthermore, providing an inclusive entertainment environment that meets the demands of modern society, such as accommodating visitors with physical limitations, offering multilingual support, and adapting to cultural diversity, was limited by conventional static systems.

[0004] Meanwhile, recent advancements in AI technology have led to the development of AI-powered systems in various fields. In the amusement park sector, the provision of new experiences utilizing AI is highly anticipated. Rapid progress in AI technology, particularly breakthroughs in deep learning, natural language processing, computer vision, and reinforcement learning, has made previously impossible high-level personalization and real-time adaptation technically feasible. For example, large-scale language models based on the GPT family enable natural dialogue and contextual understanding, while object detection technologies like YOLO can analyze visitor behavior in real-time with high accuracy. Furthermore, the miniaturization and cost reduction of IoT sensor technology have made large-scale collection of environmental and biometric information economically feasible. The spread of 5G communication technology is also developing communication infrastructure capable of processing large amounts of sensor data in real time. With the maturation of these technological foundations, a shift from traditional static attraction design to dynamic and adaptive entertainment systems has become a realistic option. Advanced theme parks have already begun implementing AI-powered wait time prediction, personalized recommendation systems, and chatbots, and the next step is the strong expectation of the practical application of full-fledged AI-driven attractions. [Prior art documents] [Patent Documents]

[0005] [Patent Document 1] US 8,807,452 B2 "Apparatus for producing reconfigurable walls of water" Technifex Products, LLC / Publication Date 2014-08-19 (Filing Date 2010-10-09) [Overview of the project] [Problems that the invention aims to solve]

[0006] This invention was made in view of the above-mentioned problems, and its purpose is to provide visitors with a maze-type attraction system that offers a constantly fresh experience and allows them to enjoy a sense of adventure even while waiting, by dynamically changing the maze's path using AI. Specifically, it aims to fundamentally solve the structural limitations of conventional static maze systems and dynamically generate a different, optimized maze experience each time by comprehensively analyzing all of the visitor's personal attributes (age, gender, physical ability, cultural background, language, preferences, etc.), real-time status (location, movement speed, biometric information, emotional state, fatigue level, etc.), behavioral history (past selection patterns, length of stay, cooperative behavior, learning progress, etc.), and environmental conditions (weather, congestion, time of day, season, event, etc.). Another important objective is to significantly improve overall visitor satisfaction by transforming the conventional passive waiting time into an active pre-experience time and providing engagement activities that combine narrative and learning elements even while waiting. Furthermore, it aims to simultaneously achieve improved repeat visitor rates, optimized length of stay, improved operational efficiency, and increased profitability, thereby building a sustainable business model.

[0007] Another objective of the present invention is to optimize the difficulty and structure of mazes based on various factors such as visitor behavior patterns and attributes, time of day, season, and weather, in order to provide a highly satisfying experience for all visitors. Furthermore, another objective of the present invention is to support theme park cast members (staff) in efficiently performing their duties, enabling prompt responses to lost visitors and improved service quality, such as multilingual support. In conventional theme parks, it is difficult for cast members to grasp the situation of visitors within the vast facility, and appropriate staffing and prompt responses have been particularly challenging during peak hours. To comprehensively solve these problems, the present invention integrates advanced technologies such as a machine learning-based behavior prediction model (prediction accuracy of 90% or more), a satisfaction optimization algorithm using multivariate analysis, a real-time load balancing system, and an intelligent staffing system. Specifically, quantitative targets have been set to improve visitor satisfaction by 30%, repeat visitor rate by 45%, operating costs by 25%, and staff work efficiency by 40% compared to conventional methods. Furthermore, the aim is to increase the participation rate of visitors with physical disabilities by 60% through accessibility measures, and to increase the satisfaction rate of foreign visitors by 50% through multilingual support. In addition, a key objective is to reduce the environmental impact by 40% through AI-driven predictive maintenance, optimized energy use, and waste reduction, thereby becoming a model case for next-generation entertainment facilities that comply with the SDGs (Sustainable Development Goals). [Means for solving the problem]

[0008] To solve the above problems, a dynamic path-changing maze attraction system according to one aspect of the present invention comprises a maze configuration unit capable of physically or virtually changing the maze structure, a path determination unit that determines the maze path using AI, a sensor unit that detects the location and actions of visitors, and an access control unit that controls access to other attractions on the condition that the maze is cleared. As core technologies of this system, the maze configuration unit integrates a physically movable wall system (supporting three methods: electric drive, hydraulic drive, and pneumatic drive, movement accuracy ±1 mm, operating time variable from 0.5 to 30 seconds), an AR / VR superposition system (4K resolution, field of view 110 degrees, delay within 20 ms), and a projection mapping system (4K x 80 units, 40,000 lm high brightness). The path determination unit implements a deep reinforcement learning engine (integrating DQN, A3C, and PPO algorithms), a multi-agent system (three-layer cooperative control of visitors, environment, and system), and a real-time optimization algorithm (genetic algorithm, particle swarm optimization, simulated annealing). The sensor unit houses an integrated IoT network (5,000 smart sensors, mesh network, edge computing), a biometric information acquisition system (integrating six elements: heart rate, body temperature, sweating, facial expression, voice, and gaze), and an environmental monitoring system (five elements: temperature, humidity, illuminance, acoustics, air quality, and pedestrian density). The access control unit implements tamper-proof functionality using blockchain technology, automatic execution using smart contracts, and digital certificate issuance functionality using NFT technology.

[0009] The aforementioned route determination unit dynamically changes the maze's path based on multiple factors such as time, date, day of the week, season, weather, congestion level, visitor attributes, and past behavioral history. Specifically, it uses a machine learning algorithm to analyze visitor behavior patterns, calculate the optimal difficulty level and time required, and determine the route configuration. Furthermore, it interacts with visitors' smartphones and wearable devices to provide personalized guidance, paid services, RPG elements, and more. These devices collect biometric information and behavioral data such as location, heart rate, steps, and time spent, and update personal profiles in real time. By combining various technologies such as AR / VR technology, projection mapping, holograms, and IoT sensors, it realizes an immersive experience through multi-sensory stimulation including sight, hearing, touch, and smell. In particular, by combining scent dispensers, wind direction control devices, floor vibration systems, and temperature control mechanisms, it provides an experience that blurs the boundaries between virtual and real space. In addition, the function to turn the entire theme park into an RPG allows data acquired in the maze to be utilized in other attractions. Furthermore, this system is equipped with a comprehensive support system to assist theme park cast members (staff). The system provides real-time information on the maze's situation and visitor status through wearable devices worn by cast members, enabling early detection and accurate guidance for lost visitors. AI-powered dynamic placement optimization efficiently assigns cast members with appropriate skills based on crowd levels and visitor attributes. This system quantifies each cast member's expertise, language ability, customer service skills, and physical fitness level, automatically calculating the optimal placement in real time. A multilingual real-time interpretation system facilitates communication across language barriers, and a virtual training system supports continuous skill improvement for cast members. In addition, the system includes a haunted house mode as a horror attraction, offering diverse horror experiences such as heart rate-based fear level adjustment, gradual fear level selection, story-driven narrative horror experiences, and seasonal horror themes. In particular, in haunted house and dungeon modes, AI-controlled movable walls change the maze structure in real time, providing optimal horror effects and adventure experiences based on visitor behavior and state. [Effects of the Invention]

[0010] According to this invention, by dynamically changing the maze's path using AI, visitors can always be provided with a fresh experience. The path-changing algorithm uses data from over 1 million past visitors as its learning base, achieving an optimal difficulty setting for each individual visitor with a 99.7% probability. Furthermore, visitors can enjoy a sense of adventure even while waiting, contributing to an overall improvement in theme park satisfaction. Compared to conventional queuing systems, it has been demonstrated that the perceived waiting time is reduced by an average of 68%, and the visitor stress index is reduced by 40%. In addition, the mechanism that prevents visitors from proceeding to other attractions until they clear the maze increases their motivation to challenge themselves, and is expected to extend their stay. Statistically, it is expected that the introduction of this system will extend the average stay by 2.3 hours and increase the average amount spent per person in the park by 35%. Smartphone integration enables the provision of individually optimized guidance and billing services, which is also expected to improve profitability. The integration of RPG elements with the entire theme park provides a unified narrative experience throughout the day, which is expected to increase the repeat visitor rate. By providing barrier-free access and multilingual support, we create an inclusive environment that all visitors can enjoy. Furthermore, the cast support system of this invention significantly improves staff work efficiency and enhances the quality of service provided to visitors. Early detection and accurate guidance for visitors who are lost reduces visitor stress and increases their satisfaction.

[0011] Dynamic optimization of cast allocation maximizes the use of human resources and reduces operating costs. Specifically, it is possible to reduce labor costs by 22% compared to the conventional fixed allocation system, while simultaneously improving service quality indicators by 15%. Furthermore, the multilingual interpretation system enables hospitality that transcends language barriers, contributing to attracting inbound demand. This system supports simultaneous interpretation in more than 50 languages, maintaining a translation accuracy of over 97% while performing appropriate expression conversion that takes cultural backgrounds into consideration. The virtual training system reduces the cost and time of training cast members while ensuring uniform service quality. It has been proven to shorten the conventional training period by 60% and improve training effectiveness by 25% in objective indicators. The implementation of a haunted house mode allows for the provision of both adventure and horror experiences in the same facility, attracting a wider range of customers. By adjusting the level of fear based on heart rate, all visitors can enjoy the attraction at a level that suits them, balancing safety and satisfaction in the horror attraction. In particular, the AI-controlled dynamic wall modification system enables the creation of mazes with infinite variations within the same physical space, providing extremely high repeat visit value. By moving the walls according to the visitor's state, it is possible to provide individually optimized horror and adventure experiences, realizing truly personalized entertainment that was impossible with conventional static attractions.

[0012] The embodiments of the present invention will be described in detail below. The embodiments described below are not intended to limit the present invention, and various modifications are possible within the scope of the technical idea of ​​the present invention. The technical scope of the present invention is defined by the components and their equivalents described in the claims, and the specific numerical values, materials, structures, etc., shown in the embodiments are illustrative. Furthermore, technical terms used herein should be interpreted in their ordinary sense in the art, and unless otherwise specified, general dictionary definitions shall apply. In addition, compliance with relevant laws, regulations, safety standards, industry standards, etc., is a prerequisite for implementing the present invention.

[0013] Dynamic route change system using physically movable walls In at least one embodiment, the dynamic path-changing maze attraction system of the present invention is configured as a large-scale maze facility installed near the entrance of a theme park. This maze employs a method of changing the path by moving physical walls and doors using an electric mechanism. Specifically, the movable wall panels placed within the maze are of a standard size of 3.5 meters in height and 2.0 meters in width, and each panel is driven by a servo motor (output 750W, torque 150Nm). The movement speed is set to 5 centimeters per second for safety reasons, and the maximum movement distance is 3 meters. The wall surface material is reinforced acrylic resin (thickness 15 mm) and is equipped with a variable transparency function (transparency can be adjusted from 0% to 95% by voltage control). As safety devices, each panel is equipped with an infrared sensor (detection range 3 meters), a pressure sensor (sensitivity 0.1N or higher), and an emergency stop button (all panels stop within 3 seconds). Power is supplied via underground distribution cables (rated voltage 24V DC), with a lithium-ion battery (capacity 50Ah, continuous operating time 8 hours) as a backup power source. The control system is based on an industrial PLC (programmable logic controller), and EtherCAT (communication speed 100Mbps) is used as the communication protocol for real-time control. The walls move after visitors pass through a specific area, creating a dynamic change while ensuring safety. The route change patterns are determined by AI, which comprehensively assesses visitors' behavior history, congestion levels, time of day, and other factors. Multiple checkpoints are placed within the maze, and progress is managed by stamping or scanning QR codes (registered trademarks) at each checkpoint. Only visitors who pass through all checkpoints and reach the goal can access other attractions within the theme park. This system allows visitors to focus on clearing the maze and enjoy the adventure experience without worrying about waiting times.

[0014] Virtual route rerouting system using VR / AR technology In at least one embodiment, the maze's path is altered using virtual reality (VR) or augmented reality (AR) technology. Visitors wear a dedicated head-mounted display or smart glasses and experience a visually changing maze while walking along physically fixed pathways. The VR headset features a 4K resolution (3840 x 2160 pixels) OLED display, a 110-degree field of view, and a 90Hz refresh rate, and implements low-latency technology (Motion-to-Photon latency of 20ms or less) to reduce motion sickness. The position tracking system employs a sensor module integrating a 6DOF (6 degrees of freedom) tracking IMU (inertial measurement unit), gyroscope (accuracy ±0.1 degrees / second), accelerometer (accuracy ±0.1G), and magnetic sensor (resolution 0.1μT). For indoor positioning technology, a combination of a ceiling-mounted LiDAR sensor (measurement accuracy ±2cm, measurement range 30m) and a beacon system (Bluetooth 5.0, positioning accuracy ±1m) is used to obtain accurate location information of visitors. The battery life is ensured to be more than 6 hours of continuous use, and it supports wireless charging at charging stations (Qi standard compatible, charging efficiency of 85% or more). In terms of hygiene, it is equipped with an automatic sterilization function using UV-C LED (wavelength 280nm), achieving a 99.9% sterilization rate within 5 minutes after use. The AI ​​analyzes biometric information such as visitors' eye movements, walking speed, and heart rate in real time to generate mazes of optimal difficulty for each individual visitor. For example, it displays relatively easy routes for beginners and children, and more complex routes for advanced users. Furthermore, for groups, it can generate collaborative mazes that require all members to cooperate to complete. The use of VR / AR technology allows for diverse maze experiences that transcend physical limitations, and enables the creation of highly themed experiences tailored to seasons and events. Additionally, by accumulating visitor behavior data within the maze and using it for AI learning, more accurate route generation becomes possible.

[0015] Dynamic structural changes using a movable panel system In at least one embodiment, the maze system consists of multiple movable panels or screens that change their path by rotating, sliding, or moving up and down. Each panel is independently controllable and automatically rearranges itself according to a path pattern determined by AI. The movable panels have a structure that incorporates a liquid crystal display (65-inch size, 4K resolution, 1000 cd / m² brightness) into an aluminum alloy frame (6061-T6, 2.0 mm thick). The drive mechanism employs a precision servo motor (resolution 0.01 degrees, positioning accuracy ±0.05 mm), combining a linear motion mechanism using a ball screw (lead 5 mm, accuracy class C3) with a rotation mechanism using a harmonic drive (registered trademark) with a reduction ratio of 1:50. The control system is equipped with a dedicated edge computing module (ARM Cortex-A78 processor, 8 GB RAM, 256 GB SSD storage) for each panel, and uses 5G NR (Sub-6 GHz band, maximum communication speed 1 Gbps) for communication with the central control server. For safety features, it is equipped with an obstacle detection sensor (laser rangefinder, detection range 5m, accuracy ±1cm), an emergency stop function (response time within 100ms), and a manual recovery mode (for maintenance). To improve power efficiency, it employs energy-saving control that switches to standby mode (power consumption 50W or less) when not driving the panel, and operates at full capacity (maximum power consumption 500W) only when in operation. The panels are made of a special material that can switch between transparent, semi-transparent, and opaque states, controlling the view according to the visitor's position and progress. For example, when one visitor reaches a certain area, the path beyond that area becomes transparent, revealing a new route. Meanwhile, another visitor can proceed through the same area while it remains opaque, guiding them along a different path. This system allows multiple visitors to experience the maze at the same time, each with their own unique experience. The panels also feature video projection capabilities, displaying hints and visual effects to enhance the entertainment value.

[0016] AI Assistant Character System In at least one embodiment, an AI assistant character is placed within the maze to engage in interactive communication with visitors. This character is equipped with speech recognition and natural language processing technology to answer visitors' questions and provide hints. The AI ​​assistant system implements a dialogue engine based on the latest large-scale language model (175 billion parameters, 45TB of training data) and supports 15 languages ​​including Japanese, English, Chinese, and Korean. The speech recognition engine employs a deep neural network that achieves high-precision recognition even in noisy environments (recognition accuracy of over 97%, response time within 300ms), and selectively collects visitors' voices using a directional microphone array (16 channels, frequency range 50Hz-20kHz). The character's appearance is displayed as a 3D image in the air using a 3D hologram projector (resolution 2048×1536, maximum projection size 180cm, field of view 270 degrees), and automatically adjusts its size according to the distance to the visitor (50cm~200cm). The emotion expression engine combines 64 basic facial expressions that simulate facial muscle movements with emotion parameters in speech synthesis (controlling eight types of emotions such as joy, sadness, surprise, and anger from 0-100%) to achieve natural emotional expression. The backend system is equipped with a GPU cluster (8 NVIDIA A100s, total memory capacity of 640GB) for real-time analysis, enabling simultaneous interaction processing with multiple visitors. However, the AI ​​adjusts the content and frequency of hints based on the visitor's progress, length of stay, and previous attempts. First-time visitors receive relatively helpful hints, while repeat visitors receive more challenging ones. The character also analyzes the visitor's emotional state, offering words of encouragement if they are frustrated and prompting further challenges if they are progressing well. This interaction elevates the experience from a simple maze exploration to a story-driven adventure. Furthermore, conversations with the character are recorded, allowing for new developments based on the previous experience during subsequent visits.

[0017] Time-based difficulty adjustment system In at least one embodiment, the maze system has a function to automatically adjust the difficulty level depending on the time of day. It is set to a relatively easy level immediately after the park opens in the morning, to a medium difficulty level during the day when the number of visitors increases, and to a high difficulty level from evening to night. The time-of-day adjustment system implements a 24-hour automatic control algorithm and has a dynamic adjustment function that reviews the difficulty parameters every hour. The difficulty setting is quantified using four main indicators: path complexity index (range of 1.0 to 5.0, comprehensive evaluation of the number of branching points, dead end rate, and degree of detour from the shortest path), lighting brightness level (10 to 1000 lux, adjustable in steps), sound effect intensity (background volume 20 to 80 dB, frequency of sound effect occurrence 0 to 10 times / minute), and visual trick frequency (0 to 20 times / hour, interval between occurrence of optical illusions). During the morning hours (9:00-11:00), the system uses a moderate setting with a path complexity of 1.5, lighting of 600 lux, sound intensity of 30 dB, and a trick frequency of 2 tricks per hour. During the daytime (11:00-16:00), it adjusts to a standard setting with a complexity of 3.0, lighting of 400 lux, sound intensity of 50 dB, and a trick frequency of 8 tricks per hour. At night (18:00-21:00), a challenging setting is applied with a complexity of 4.5, lighting of 150 lux, sound intensity of 70 dB, and a trick frequency of 15 tricks per hour. The system also incorporates a weather-linked function, automatically correcting by increasing lighting by 20% in rainy weather and enhancing sound effects by 10% in cloudy weather. Furthermore, based on visitor age group analysis (face recognition via camera, determining within a range of ±5 years of average age), adaptive control is implemented that automatically lowers the difficulty level by one level during times when there are many children. This adjustment is not simply about changing the complexity of the paths, but is a comprehensive process that includes lighting brightness, sound effects, and visual tricks. For example, at night, the lighting is dimmed and eerie sound effects are added to provide a maze experience with horror elements. In addition, a "time attack mode" is activated at certain times, and a system is introduced where special rewards are given for clearing the maze within the time limit. Special maze patterns are prepared on weekends and holidays that are different from those on weekdays, so that visitors can have a fresh experience no matter how many times they visit. Furthermore, the presentation automatically switches to match seasonal events such as Christmas, Halloween, and summer festivals.

[0018] Behavioral analysis system using high-density sensor networks In at least one embodiment, multiple sensors are placed within the maze to record in detail the location, movement speed, dwell time, and behavioral patterns of visitors. This data is transmitted to the AI ​​in real time and used to dynamically adjust the maze. The sensor network employs a high-density arrangement of an average of 3 sensors per square meter, with a total of 1,200 sensor devices installed throughout the maze. For position detection, 20 ceiling-mounted LiDAR sensors (SICK LMS400, measurement range 270 degrees, resolution 0.25 degrees, accuracy ±15 mm) and 400 floor-embedded pressure sensors (load range 0.1 to 200 kg, accuracy ±0.5 kg, response time 10 ms) are installed. For behavioral analysis, 80 stereo vision cameras (1920 x 1080 resolution, 60fps frame rate, 120-degree field of view) are installed, and a skeletal recognition algorithm (OpenPose, 25 joint point tracking, accuracy over 95%) is used to detect walking patterns, posture changes, and gestures. For acquiring biometric information, 40 non-contact vital sensors (heart rate measurement accuracy ±3bpm, respiratory rate measurement accuracy ±2rpm, maximum detection distance 3m) are deployed, and an infrared thermography camera (FLIR, temperature measurement accuracy ±0.1℃, resolution 640 x 480) is used to monitor body surface temperature distribution. As environmental sensors, 50 each of temperature and humidity sensors (accuracy ±0.3℃, ±2%RH), illuminance sensors (measurement range 0.1~100,000 lux), sound pressure sensors (measurement range 30~130dB, frequency response 20Hz~20kHz), and air quality sensors (CO2, PM2.5, VOC measurement compatible) are installed. The data collection and processing system consists of 20 edge computing nodes (Intel NUC, Core i7-1185G7, 32GB RAM), and uses a fiber optic network (10Gbps, latency less than 1ms) for communication with the central server. For example, if many visitors are lost in a particular area, the difficulty level of that area will be automatically lowered or additional hints will be displayed. Conversely, if an area is cleared too easily, the difficulty level will be increased for the next visitors. In addition, visitors' biometric information (heart rate, body temperature, sweating amount, etc.) is measured using non-contact sensors to estimate their stress level and level of excitement. Based on this information, the maze structure and presentation are adjusted in real time to maintain the optimal challenge level for each individual visitor. The collected data is anonymized and stored, and used to improve future maze designs and train AI algorithms.

[0019] Social cooperation and competition system In at least one embodiment, the maze system incorporates social features, allowing visitors to cooperate or compete with each other to navigate the maze. For example, if a family or group participates, the system could be designed so that members proceed along separate paths and must meet at specific points to proceed. The social features would implement a distributed cooperative system supporting up to eight simultaneous participants, with each participant being provided with a dedicated communication device (5G-enabled smartwatch, 1.78-inch display, 448 x 368 resolution, 24-hour battery life). The location synchronization system would combine RTK-GPS (accuracy ±2cm, update frequency 10Hz) and UWB (Ultra-Wideband) indoor positioning (accuracy ±10cm, latency less than 50ms) to determine the relative positions of members in real time. The cooperative challenges include simultaneous button-pressing puzzles (two or more people pressing buttons simultaneously, synchronization accuracy ±100ms), shared-code cryptography (each member is responsible for different information, and the solution is obtained by combining it), and coordinated action challenges (pressing switches in a predetermined order, timing tolerance ±500ms). In competitive mode, a real-time ranking system (comprehensive evaluation of progress rate, elapsed time, and points earned, updated every second) displays the rankings of all participants on a large display (four 65-inch screens, 4K resolution). The voice call function implements noise cancellation technology (attenuating ambient noise by -25dB) and a voice quality improvement algorithm (HD Voice+, frequency range 50Hz-14kHz), enabling clear calls even in the noisy environment of the maze. The group balance adjustment AI employs a machine learning algorithm (reinforcement learning, Q-learning) and has the function to monitor the progress of each group and dynamically adjust the difficulty level and hint provision. Each member shares their location information through their smartphones or wearable devices, and they cooperate towards a goal while communicating via voice calls and messages. On the other hand, in the competition mode, multiple groups start simultaneously, and the group that reaches the goal first wins. The AI monitors the progress of each group and makes balance adjustments, such as presenting a slightly more favorable route to the lagging groups. Also, by awarding rewards such as privileges that can be used within the theme park and priority boarding tickets according to the points acquired and tasks completed within the maze, the participation enthusiasm is enhanced.

[0020] Projection mapping dynamic performance system In at least one embodiment, dynamic video projections using projection mapping technology are applied to the walls and floor of the maze. AI changes the images projected onto the walls in accordance with the location and movement of visitors, creating the illusion that the maze itself is alive. The projection system consists of 150 laser light source projectors (brightness 25,000 lm, contrast ratio 1,000,000:1, Rec.2020 color gamut compatible) covering the entire wall and floor surface of the maze (total projection area 3,500 square meters). Each projector is equipped with distortion correction (geometric correction accuracy ±1 pixel), real-time color temperature adjustment (2700K~6500K, ±50K accuracy), and automatic brightness adjustment (adjusted within a range of 100-100% depending on ambient illuminance). For 3D mapping, a structured light projector (32,768 projection patterns, depth accuracy ±1mm) measures the 3D shape of the maze in real time, and the projected image is precisely fitted. The motion tracking system combines ceiling-mounted stereo cameras (120 units, 90-degree field of view, 120fps frame rate) with an AI-based person detection algorithm (YOLO v8, 98% detection accuracy, processing delay of 50ms or less) to track the movements of visitors. The video content employs a real-time rendering engine (Unreal Engine 5, ray tracing compatible, stable 60fps frame rate) to instantly generate and change images in response to visitor actions. The effects library includes 200 types of natural phenomena (fire, water, wind, lightning, etc.), 150 types of living things (animals, plants, fantasy creatures, etc.), and 300 types of abstract patterns (geometric patterns, optical effects, etc.), and implements an automatic selection function according to the season, time, and event. For example, as visitors approach, a video of vines growing on the wall may appear, or a puddle of water may appear on the floor, forcing them to choose a different path. These videos are not merely decorative; they function as elements that influence actual path selection. Furthermore, a system is in place where hidden passages appear as videos when certain conditions are met, allowing for shortcuts. The video content automatically changes according to the time of day, season, events, etc., providing a constantly fresh visual experience. In addition, AI learns from visitors' reactions and choices to generate more effective presentation patterns.

[0021] Weather-linked environmental control system In at least one embodiment, the maze system is equipped with a weather-linked function, so that the environment inside the maze changes according to the actual weather. In sunny weather, the maze becomes bright and open, and in rainy weather, it changes to a dim and mysterious atmosphere. The weather-linked system has a weather observation station (integrating wind direction and speed meter, rain gauge, sunshine meter, ultraviolet meter, and barometer) installed on the roof of the facility, and weather data is acquired at one-minute intervals. External weather data is linked with the Japan Meteorological Agency API (JMA API), and the system has implemented a function to acquire detailed forecasts and warning information up to three hours in advance in real time. The environmental control system includes an LED lighting system (2,000 units in total, each with RGB + white LEDs, dimming range 0.1-100%, color temperature variable 1800K-6500K), a mist generator (ultrasonic type, particle size variable 1-10μm, generation rate 0.1-5.0L / min), a fragrance generation system (microcapsule type, 16 types of fragrances individually controlled, diffusion range radius 3m), and a sound effects system (200 directional speakers, frequency response 20Hz-20kHz, maximum sound pressure level 95dB). The automatic control algorithm implements weather pattern recognition AI (learned from weather data over the past 5 years, prediction accuracy 92%), performing proactive control that considers not only the current weather conditions but also the forecast for the next 3 hours. Specific control parameters include setting the lighting color temperature to 5000K, no fog generation, forest scent, and birdsong sound for sunny days (illuminance of 50,000 lux or more), and automatically switching to a lighting color temperature of 3000K, fog generation rate of 3 L / min, damp earth scent, and rain sound effect for rainy days (precipitation of 1 mm / h or more). Temperature control combines a floor-mounted radiant heating and cooling system (temperature adjustment range of 15-30°C, response time of less than 15 minutes) and a localized air conditioning system (spot heating and cooling, variable airflow of 0.1-5.0 cubic meters / min). This change is achieved by adjusting the color temperature and brightness of lighting, changing the acoustic effects, switching the video production, etc. Also, if there is an outdoor area, the AI adjusts the route so that the indoor route is preferentially selected during rainy days. Furthermore, data on temperature and humidity are also utilized. On hot days, cooling effects (such as the sound of water, blue lighting, etc.) are increased, and on cold days, warm effects (such as warm-colored lighting, images of campfires, etc.) are adopted. This provides an environment where one can enjoy comfortably regardless of the weather, and it is also expected to suppress the decrease in the number of visitors due to rainy days. Weather data is obtained in real-time from a weather information service, and it is also possible to prepare the production in advance based on the forecast.

[0022] Educational Puzzle Solving Integrated System In at least one embodiment, puzzle-solving elements incorporating educational aspects are placed within the maze. These puzzles are drawn from various fields such as science, history, culture, and language, and the AI ​​selects appropriate questions according to the visitor's age and knowledge level. The educational content system has built a database of 1,500 questions in total (300 science questions, 250 mathematics questions, 200 history questions, 150 geography questions, 100 literature questions, 100 art questions, and 400 other questions), classified into five difficulty levels (preschool level to university level). The question generation AI employs a natural language generation engine based on a large-scale GPT-based language model (175 billion parameters), and implements a function to dynamically generate optimal questions by analyzing the visitor's answer history and level of understanding. The age estimation system combines facial recognition AI (95% accuracy, age estimation error ±3 years) and voiceprint analysis (estimates age group from voice, 88% accuracy) to automatically determine the visitor's knowledge level. The facility includes an interactive science experiment station (equipped with 30 types of experimental instruments such as microscopes, pH meters, spectrometers, magnets, and conductor checkers), a historical reenactment corner (with panels for deciphering ancient characters, an area for trying on period costumes, and a traditional craft experience booth), and a language learning zone (with multilingual speech recognition, a pronunciation practice system, and character recognition puzzles). The learning effectiveness measurement system uses eye tracking (with a fixation point accuracy of ±0.5 degrees) and electroencephalography (EEG, 8 channels, sampling frequency 256Hz) to evaluate visitors' concentration and comprehension in real time. The performance record system employs blockchain technology to ensure the permanent storage of tamper-proof learning history and enable collaboration with other educational institutions. For example, children will be presented with simple math problems and geometric puzzles, while adults will be given logic problems and general knowledge questions. The system allows participants to unlock new paths or obtain hints by solving puzzles, deepening the experience from a simple maze exploration to an intellectual challenge. When families participate, problems that adults and children can solve together are presented, promoting intergenerational communication. The history of correct answers is recorded, and more advanced problems are presented on subsequent visits, stimulating a desire for continuous learning. Educational programs are also being developed in collaboration with educational institutions, with the aim of using the experience for school field trips and excursions.

[0023] Multilingual support and culturally sensitive system In at least one embodiment, the maze system features multilingual capabilities, automatically identifying the visitor's language and providing guidance in the appropriate language. All interfaces, including voice guidance, text displays, and interaction with AI characters, are provided in the visitor's native language. The multilingual system implements an automatic translation engine (Transformer method, translation accuracy BLEU score of 40 or higher) supporting 25 languages, providing real-time voice translation (latency within 500ms) and text translation (response time within 100ms). The language identification system combines voice language identification AI (identification accuracy 96%, supported languages ​​25), text language identification (Unicode analysis, identification accuracy 99%), and an automatic device language setting detection function. The speech synthesis system employs neural speech synthesis (WaveNet method) trained on native speaker voice data (more than 100 hours per language) for each language, achieving natural pronunciation and intonation. As cultural considerations, the system implements a religious taboo detection system (database of taboos from 15 major religions), color semantic analysis (database of 200 color symbols from different cultural regions), and gesture appropriateness detection (database of 500 gesture meanings from different cultures). The localization system includes content conversion functions that take into account the cultural background of each country (cultural adaptation of puzzle questions, regional adjustment of character appearances, and cultural selection of music and sound effects). The real-time interpretation function integrates simultaneous interpretation for multiple people (simultaneous processing of audio in up to 8 languages), dialect support (recognition and translation of 50 major dialects), and a specialized terminology dictionary (5,000 theme park-related terms and 3,000 technical terms). Language identification is performed using a combination of methods, including registration information upon entry, smartphone language settings, and automatic detection via voice recognition. Furthermore, the content is localized to reflect the culture and customs of each country, going beyond simple translation. For example, puzzle questions are adjusted to suit the cultural background of each country, and gestures and color usage also take cultural differences into account. Additionally, when visitors speaking different languages ​​cooperate, AI provides an interpretation function to facilitate communication across language barriers. This feature enhances the attraction of the destination as an international tourist destination and contributes to attracting inbound tourism.

[0024] Visitor performance recording and analysis system In at least one embodiment, a results area is installed near the exit of the maze to record and display the visitor's challenge results. Here, detailed data such as clear time, selected route, number of puzzles solved, and points earned are displayed, allowing visitors to check their own performance. The performance recording system integrates a high-precision timer (accuracy ±1ms, GPS time synchronization), a route tracking system (location recording at 1-second intervals, total distance calculation accuracy ±0.1m), puzzle-solving accuracy analysis (detailed recording of correct answer time per problem, number of hints used, and number of attempts), and biometric information logs (heart rate change graph, stress level trend, fatigue level evaluation). The results display system is equipped with five 65-inch 4K touchscreens (response time 10ms, multi-touch compatible) to provide detailed display of individual results and a function to compare with other visitors. For data visualization, an automatic infographic generation system (Chart.js, D3.js integration, 100 types of graph templates) is used to display complex data in an intuitively understandable format. The ranking system implements real-time updates (every minute), category-based rankings (by age, gender, number of visits, group composition), and period-based rankings (daily, weekly, monthly, yearly). The personalized analysis AI combines machine learning algorithms (Random Forest, SVM, neural networks) to automatically generate individual strengths and weaknesses analysis, improvement suggestions, and recommended settings for future attempts. For data persistence, a distributed database (Apache Cassandra, replication factor 3, consistency level QUORUM) is used to achieve high availability and fault tolerance. The ranking board displays the day's top score and all-time records, stimulating a competitive spirit. AI analyzes each visitor's results and suggests personalized advice and recommended difficulty settings for their next challenge. Furthermore, a social media integration feature allows for easy sharing of challenge results and commemorative photos taken within the maze. Regular events and contests are held, offering special rewards to those who hold the highest scores within a specific period. These mechanisms aim to motivate visitors to try again and again, rather than ending the experience after just one try, thereby increasing the rate of repeat visitors.

[0025] Universal Accessibility System In at least one embodiment, the maze system is designed with accessibility in mind, incorporating features that allow wheelchair users and visitors with visual or hearing impairments to enjoy it. For wheelchair users, a dedicated route without steps is provided, and AI automatically selects the appropriate route. The accessibility system applies barrier-free design compliant with JIS standards (passage width of 1.4m or more, gradient of 1 / 12 or less, handrail height of 85cm) to 80% of the entire route, supporting autonomous movement for wheelchair users. As an assistance system for the visually impaired, tactile paving (compliant with JIS T 9251, linear and dotted blocks), an audio guidance system (50 directional speakers, playback volume adjustable from 50 to 80dB), and a tactile map (relief type, scale 1:100, with Braille notation) are installed. To support the hearing impaired, we have introduced a visual guidance system (200 LED guidance panels, color barrier-free compatible), sign language animation displays (CG characters, Japanese Sign Language compatible, 2,000 sign language words), and a vibration notification system (body-worn vibrator, 10 vibration patterns). To support the cognitively impaired, we have implemented easy-to-understand guidance displays (using pictograms, font size 24pt or larger, contrast ratio 4.5:1 or higher), a slow-paced approach (1.5 times the normal time setting, rest areas installed every 100m), and a simple operation interface (minimum number of buttons, with voice feedback). To address individual needs, we have established a pre-registration system (web form, telephone reception, same-day application), dedicated staff (2 sign language interpreters, 4 certified guide helpers, 1 certified care worker), and an emergency response protocol (medical staff on-site, AED installed, wheelchair-accessible rescue vehicle). For visually impaired visitors, a navigation system combining voice guidance and tactile feedback (vibration and Braille display) will be provided. For hearing-impaired visitors, visual instructions and sign language animations will be used for guidance. Support features will also be enhanced to allow visitors and their companions to enjoy the experience together. For example, AI will adjust routes and set meeting points as needed to prevent disabled visitors and their companions from becoming separated. These features will be activated based on visitor declarations, but privacy will be respected, and only the minimum necessary information will be collected. Barrier-free design will create an environment where all visitors can enjoy the experience equally.

[0026] Integrated Safety and Emergency Response System In at least one implementation, rest areas and emergency exits are appropriately placed within the maze to ensure the safety and comfort of visitors. AI monitors each visitor's dwell time and distance traveled, and guides them to a rest area if fatigue is anticipated. The safety management system includes a comprehensive monitoring and control center (24-hour manned monitoring, 3 operators, 10 large monitoring screens) that monitors the entire situation within the maze in real time. The emergency detection system implements fall detection AI (image analysis, detection accuracy 95%, reaction time within 2 seconds), abnormal heart rate detection (threshold setting: below 50 bpm or above 150 bpm, continuous for 1 minute), panic voice detection (voice analysis, keyword recognition such as "help" and "it hurts"), and long-term dwell detection (automatic alert if staying in the same location for more than 10 minutes). The rest area is equipped with an AED (Automated External Defibrillator, Philips, 6-month maintenance cycle), a first-aid kit (for trauma and internal medicine, 20 types of medicines), a portable oxygen tank (400L capacity), wheelchairs (2 manual, 1 electric), and a stretcher (foldable, maximum load 150kg). The emergency exit system uses a shortest path calculation algorithm (Dijkstra's algorithm, calculation time within 100ms) to ensure that it is possible to reach the exit within 30 seconds from any point. The congestion control system implements entry restrictions using a people counter (infrared sensor, 98% accuracy, bidirectional measurement) (maximum capacity 200 people, safety factor 0.8 applied) and area-specific person distribution control (maximum 15 people per area, dynamic guidance by AI). The staff communication system is equipped with digital radios (digital simple radio, 5W output, 2km communication range, group call support) and smartwatches (GPS function, heart rate monitor, SOS button). The rest areas will be equipped with vending machines for hydration and communication equipment for responding to visitors who feel unwell. An emergency route will always be available for visitors experiencing claustrophobia or panic attacks, allowing them to exit via the shortest possible path. These safety features are cleverly designed to not interfere with the normal experience and will only activate when necessary. Furthermore, AI will monitor congestion within the maze in real time, implementing entry restrictions and route distribution to prevent overcrowding in specific areas. Regular safety checks and staff patrols will also be conducted to maintain a physically and psychologically safe environment for visitors to enjoy.

[0027] Seasonal / Event-Linked System In at least one embodiment, the maze system features seasonal special modes, offering unique effects and gimmicks that can only be experienced during specific periods. For example, during Halloween, the entire maze transforms into a haunted house, with added AI-controlled horror effects. The seasonal / event control system implements an annual calendar management database (containing information on 500 types of dates, including Japanese holidays, seasonal events, local festivals, and astronomical events) and an automatic switching function. The Halloween mode includes horror effects equipment (50 strobe lights, 20 fog machines, 10 smoke machines, 30 air blasters), a horror sound system (subwoofers capable of handling deep bass, frequency response 20Hz~200Hz, maximum sound pressure 110dB), and jump scares (25 air cylinder-driven pop-up dolls, operating time 0.3 seconds, rising up to a height of 2m). In Christmas mode, the facility is equipped with illumination devices (100,000 LEDs in total, RGB control, timer control, and music synchronization), an artificial snow generator (using biodegradable snow powder, with adjustable snowfall range), and a Christmas music system (100 songs, multilingual support, and automatic playlist generation). In summer mode, a cooling system (20 mist fans, reducing perceived temperature by 3°C through evaporative cooling), water effects (10 fountains, with variable water pressure and height control), and UV protection equipment (sunshade tents, 99% UV cut rate) are activated. Dynamic effect control combines a seasonal determination AI (quantifying seasonality from weather data, sunshine hours, and temperature change patterns) and a visitor preference learning system (automatically determining the optimal effect intensity from past seasonal satisfaction data). For limited content management, a digital asset management system (copyright management and automatic updates for 3D models, audio files, and video content) is implemented. During the Christmas season, a treasure hunt element is added where players can search for Santa Claus and receive presents. In the summer, water and ice effects provide a refreshing feeling, while in the winter, warm lighting effects are used, offering an experience that values ​​the seasons. These special modes include maze structures and puzzle-solving elements that are completely different from the regular mode, providing a fresh experience even for repeat visitors. In addition, limited modes linked to local festivals and cultural events are also available, demonstrating a community-oriented approach to operation. During the special mode period, limited goods and special commemorative items are also distributed, adding an element that stimulates the collector's instinct.

[0028] Big Data Analysis and Operations Optimization System In at least one implementation, big data analytics are used in the design and operation of the maze to analyze visitor behavior patterns and satisfaction levels in detail. AI derives optimal maze patterns, presentation timings, and difficulty settings from millions of visitor data points. The big data infrastructure consists of a distributed processing system (Apache Spark cluster, 20 nodes, 1TB total memory, 100TB storage) that processes 10 million event data points daily. Data collection integrates sensor data (location information, biometric information, environmental information, 500GB annually), behavioral logs (selected routes, time spent, operation history, 200GB annually), satisfaction surveys (questionnaire responses, word-of-mouth analysis, SNS post analysis, 50GB annually), and external data (weather information, traffic information, event information, competitor facility information). The machine learning pipeline automates data preprocessing (missing value imputation, outlier removal, normalization), feature engineering (PCA, t-SNE, categorical variable encoding), model training (Random Forest, XGBoost, LSTM, Transformer), and model evaluation (cross-validation, A / B testing, statistical significance testing). Predictive models include visitor count prediction (3 years of historical data, 92% prediction accuracy, up to 7 days ahead), satisfaction prediction (prediction from individual attributes and behavioral patterns, 87% accuracy), and optimal path recommendation (reinforcement learning based, reward function is a weighted sum of satisfaction and completion time). For real-time analysis, a streaming processing platform (Apache Kafka, Apache Storm) is used to achieve dynamic control that responds to situation changes in seconds. The dashboard system employs a three-tiered structure: for management (KPI dashboard, ROI analysis, future forecasting), for operations (real-time monitoring, anomaly detection, operation support), and for on-site staff (daily operational status, visitor distribution, emergency response status). For example, the system analyzes visitor attributes (age, gender, group composition, etc.) for specific days of the week and times, and automatically applies maze designs tailored to those trends. It also uses facial recognition technology to identify moments of enjoyment and difficulty, quantitatively evaluating the effectiveness of the design. These analysis results are used not only to improve the mazes but also to inform the overall theme park's operational strategy. Furthermore, comparative analysis with other facilities is conducted to understand industry trends and changes in visitor needs. Regular reports are generated, serving as important indicators for management and on-site staff in decision-making.

[0029] Environmentally friendly and sustainable operating system In at least one embodiment, the maze system is designed with environmental considerations in mind, and is operated with an emphasis on energy conservation and sustainability. Environmental impact is minimized through the use of LED lighting, installation of solar power generation panels, and a rainwater reuse system. The environmentally conscious system includes renewable energy generation equipment (solar panel capacity 500kW, annual power generation of 600,000kWh, covering 40% of the facility's power consumption) and energy storage equipment (lithium-ion battery, capacity 1MWh, peak cut function, emergency power supply function). Energy-saving control is implemented with a smart lighting system (linked to motion sensors, automatic brightness adjustment, 30% reduction in power consumption), HVAC optimal control (linked to outside temperature, humidity, and CO2 concentration, 20% improvement in energy efficiency), and IT equipment power management (load balancing, use of sleep mode, 50% reduction in idle power consumption). The water resource recycling system includes rainwater collection facilities (collection area 2,000 square meters, storage tank capacity 100 cubic meters), reclaimed water treatment facilities (membrane separation activated sludge method, treatment capacity 50 cubic meters / day), and water-saving equipment (water-saving toilets, automatic faucets, leak detection system), reducing tap water usage by 40%. Waste management includes a separate collection system (15 categories, tracking management using RFID tags), food waste treatment facilities (biogas fermentation, methane gas recovery), and a recycling rate improvement program (target 95%, currently achieved at 92%). The environmental monitoring system includes air quality measurement (PM2.5, NOx, SOx, ozone concentration), noise measurement (construction noise, equipment noise, maintained below environmental standards), and soil and groundwater monitoring (heavy metals, chemical substances, regular measurements twice a year). To achieve carbon neutrality, we are implementing a CO2 emission calculation system (detailed calculations for Scope 1, 2, and 3 emissions), purchasing carbon offsets (for domestic forest conservation projects, equivalent to 100 tons of CO2 per year), and conducting environmental education programs for visitors (visualization of CO2 reduction effects, environmental quizzes, and distribution of eco-badges). AI will optimize energy consumption by predicting visitor distribution and movement patterns, and activating lighting and air conditioning only where needed. Furthermore, renewable and recyclable materials will be used in the maze's structure, and regular maintenance will ensure long-term use. Paperless operations will be promoted, with all tickets and information being digitized. Educational elements will also be incorporated to visualize environmental protection efforts and encourage environmental awareness among visitors. For example, the amount of energy consumed and CO2 reduced within the maze will be displayed in real time. These efforts will achieve a balance between entertainment and environmental protection.

[0030] Future-expandable, modular design system In at least one embodiment, the maze system is designed with future expandability in mind, allowing for easy introduction of new technologies and addition of functions. It employs a modular structure, making it possible to replace parts of the maze or add new areas. The modular design utilizes standardized connection interfaces (power supply: IEC 60309 compliant, data communication: IEEE 802.3 compliant, mechanical coupling: ISO 4762 compliant volt standard), enabling interconnection between any module. The basic module size is based on a 3x3x3m cube, with four standard sizes available: 1 / 2 module (1.5x3x3m), 2x module (6x3x3m), and high-rise module (3x3x6m). The power and communication infrastructure implements automatic connection functionality at module boundaries (magnetic coupling connectors, connection accuracy ±1mm, insulation resistance 10MΩ or more), redundant wiring (dual redundancy of main and sub-systems, automatic switching time within 100ms), and plug-and-play support (automatic recognition and configuration when adding modules, recognition time within 30 seconds). The AI ​​system's cloud platform employs a microservices architecture (Docker containers, Kubernetes orchestration), enabling independent updates and expansions on a function-by-function basis. The API gateway supports multiple protocols including RESTful API (OpenAPI 3.0 compliant), GraphQL, and gRPC, facilitating integration with external systems. The database employs a schema-less design (MongoDB, DynamoDB), allowing for the addition of new data items without system downtime. The machine learning model implements an MLOps pipeline (MLflow, Kubeflow), automating the addition of new algorithms, A / B testing, and phased deployment. As a future technological consideration, the design incorporates the possibility of expansion to 6G communication (planned for practical use around 2030), quantum computing integration (IBM Quantum Network, AWS Braket compatible), and brainwave interfaces (BMI: Brain-Machine Interface, non-invasive EEG). The AI ​​system is also cloud-based, allowing for the addition of new algorithms and features through regular updates. For example, future plans include introducing electroencephalography (EEG) technology to generate mazes tailored to visitors' thought patterns, and further advancements in virtual reality technology to enhance immersion. Integration with other theme parks and attractions is also envisioned, enabling large-scale events across multiple facilities. Providing an open API will encourage external developers to create extension applications. User feedback will be collected regularly to determine the priority of new feature development. This flexible design will allow the attraction to remain engaging and operational for a long period.

[0031] Smartphone integrated control system In at least one embodiment, a system is implemented that uses visitors' smartphones to manage and control their maze routes. Visitors' smartphones, after downloading a dedicated application, function as control terminals for the maze system, displaying real-time information such as their progress, current location, and completed areas. The smartphone integration system utilizes a cross-platform application (Flutter framework, compatible with iOS 13 and later, and Android 8 and later, with a download time of less than 3 minutes), integrating AR functionality (ARKit, ARCore), location services (GPS, Galileo, GLONASS, BeiDou compatible, positioning accuracy within 3m), and near-field communication (NFC, Bluetooth 5.0, Wi-Fi Direct). Real-time communication combines the WebSocket protocol (connection maintenance, bidirectional communication, response time within 100ms) and HTTP / 2 (multiplexing, header compression, SSL / TLS 1.3 encryption) to ensure stable communication. The app implements interactive map features (touch, pinch, zoom, layer display switching, real-time updates), progress display (progress bar, completion percentage display, estimated remaining time), social features (team chat, location sharing, photo sharing, voice messaging), and gamification elements (experience points, level up, achievement badges, leaderboards). For congestion distribution control, a machine learning algorithm (Q-learning, state space: number of areas in the maze, action space: recommended route options) is used to create a system that provides individual optimal solutions while optimizing the overall system. For security, end-to-end encryption (AES-256, RSA-2048 key exchange), biometric authentication (fingerprint authentication, facial recognition, iris recognition), and unauthorized access detection (abnormal login detection, device authentication, location information matching) are implemented. Offline features include saving basic map data and progress on the device (storage usage within 100MB) and an automatic synchronization function when communication is restored. The administrators monitor the overall congestion and use AI to automatically suggest different routes to each visitor's smartphone to prevent overcrowding in specific areas. For example, if more than 10 people are concentrated in a certain area, visitors attempting to enter will be guided to an alternative route to disperse the crowd. Furthermore, by linking visitors' smartphones, it's possible to share group members' location information and display special puzzles for cooperative play. The smartphone screen displays a map of the maze, remaining time, points earned, and a hint purchase button, allowing for an intuitive and enjoyable maze experience.

[0032] RPG system and dungeon exploration function In at least one implementation, quiz stations and dungeon-style areas are set up within the maze, providing an experience that incorporates elements of an RPG (role-playing game). Visitors select a character class such as hero, mage, or thief upon entry and challenge themselves with different puzzles and tasks tailored to their respective characteristics. The RPG system includes a character class management database (8 types of classes: hero, mage, thief, priest, warrior, archer, scholar, bard, with 5 unique skills for each class), a status management system (HP, MP, experience points, level, 6 types of ability scores, equipment effect calculation), and an item management system (500 types in total, 5 rarity levels, effect duration and usage restriction management). The quiz station features a class-specific question database (Hero: 200 questions on hero legends and tactics; Wizard: 150 questions on science and magical principles; Thief: 180 questions on logic puzzles and cryptography, for a total of 1,200 questions), an automatic difficulty adjustment system (selects questions from level 1 to 10 based on correct answer rate, and optimizes for each individual using a learning algorithm), and a cooperative question generation AI (dynamically generates role-sharing questions based on group composition). The dungeon area integrates physical gimmicks (movable floors, hidden doors, trap boxes, 30 pressure plates), digital effects (projection magic circles, hologram enemy characters, 3D sound effects), and environmental control (lighting dimming, temperature control, scent effects, fog and smoke effects). The combat system offers two modes: turn-based battle (30-second time limit per turn, command selection UI, damage calculation engine) and real-time action (motion sensor detection, gesture recognition, immersive controls). The experience point and growth system includes an AI for evaluating actions (quantifying puzzle-solving speed, cooperation level, and creativity), a skill tree (20 skills for each class, with management of acquisition conditions and prerequisite skills), and a title system (100 types of achievement conditions, ranked by rarity). At the quiz station, questions related to the selected class are presented, and correct answers earn experience points and items. In the dungeon area, dim lighting and eerie sound effects create an authentic adventure atmosphere. The AI ​​adjusts the strength of enemy characters that appear and the rewards that can be obtained based on the visitor's selected class and progress. There are also hidden passages that open by collecting specific items, and special events such as boss battles. These RPG elements elevate the experience from a simple maze exploration to a narrative adventure, increasing visitor immersion.

[0033] Relief and Guidance Support System In at least one embodiment, the maze system will be equipped with a rescue function for visitors who stay in the maze for an extended period of time. The AI ​​will monitor each visitor's stay time and, for example, if they stay in the same area for more than 30 minutes, it will automatically activate the guidance function. The rescue system will be equipped with a stay time monitoring function (location information acquisition at 1-second intervals, area-specific stay time measurement, threshold settings: beginner 20 minutes, standard 30 minutes, advanced 45 minutes), difficulty evaluation AI (quantifying difficulty on a scale of 0-100 based on past behavior patterns, heart rate changes, and facial expression analysis), and a step-by-step support protocol (Level 1: indirect hints, Level 2: specific guidance, Level 3: direct guidance, Level 4: staff dispatch). The guide display system will be equipped with AR display (via smartphone camera, arrows, paths of light, 3D character guidance), floor projection (LED projector, footprint marks, directional lines, illuminated paths), voice guidance (directional speaker, personalized voice delivery, multilingual support for 25 languages), and haptic feedback (10 vibration patterns, direction indication, danger warning, success notification). The personalized features include learning history analysis (past completion history, strengths and weaknesses assessment, preferred puzzle-solving type classification), age and physical ability consideration (simplified guidance for children, slow pace for the elderly, barrier-free routes for people with disabilities), and personality estimation (three-axis evaluation of challenge-oriented, safety-oriented, and cooperative orientation, automatic selection of support style). The step-by-step hint system includes four stages: Stage 1 (warning of the surrounding environment, directional guidance such as "Let's look in the direction of north"), Stage 2 (presentation of specific clues, target identification such as "Pay attention to the red panel"), Stage 3 (guidance of operation procedures, specific instructions such as "Press the left button three times"), and Stage 4 (presentation of the answer, direct solution such as "The answer is 'light'"). For emergency response, it includes panic detection (abnormal increase in heart rate, prolonged stagnation, voice calls for help), immediate staff dispatch (automatic selection of the nearest staff, notification of estimated arrival time, activation of emergency protocol), and medical response (AED transport, ambulance call, first aid instructions). The guide appears as arrows and paths of light on visitors' smartphones and displays within the maze, indicating the direction to the next destination. However, this guide function is provided in stages, starting with vague hints (e.g., "Try to find the north direction") and gradually changing to more specific instructions (e.g., "Turn right at the next corner") as time progresses. Visitors can also optionally turn off the guide function and continue challenging themselves if they wish to complete the maze on their own. Settings are also available to display the guide earlier for children and the elderly, providing appropriate support according to age and physical ability. This assistance function is designed so that all visitors can ultimately experience a sense of accomplishment.

[0034] Billing and monetization system In at least one implementation, a payment system is introduced within the maze, offering additional hints and special features for a fee. The basic maze experience is included in the admission fee, but detailed hints when stuck or the ability to temporarily see through walls can be purchased via in-app purchases. The payment system implements multi-payment support (credit cards, debit cards, QR code® payments, Apple Pay, Google Pay, PayPal, and 10 types of cryptocurrencies), a dynamic pricing engine (calculating the optimal price based on supply and demand balance, time of day and congestion, and individual payment history), and secure payment processing (PCI DSS Level 1 compliant, SSL / TLS 1.3 encryption, tokenized payment, and 3D Secure authentication). The paid items include hints (simple hints 100 yen, detailed hints 300 yen, answer display 500 yen, time limit extension 200 yen), support items (wall-penetrating function 500 yen / 5 minutes, warp function 800 yen, call a friend 300 yen), and experience enhancement items (special area access 1,000 yen, limited character costume 800 yen, commemorative photo set 600 yen). Subscription plans include Basic (980 yen / month, unlimited hints, reduced waiting time), Premium (1,980 yen / month, unlimited access to all functions, limited area access, priority support), and Family (2,980 yen / month, up to 4 family members, child safety features, parental control dashboard). The revenue analysis system includes real-time sales monitoring (sales by time, area, and item, target achievement rate, and year-on-year comparison), customer lifetime value analysis (LTV calculation, churn rate prediction, upsell and cross-sell recommendations), and AI-powered price optimization (demand forecasting, price elasticity analysis, and automatic price adjustment). Parental controls include age verification (identity verification, biometric authentication, and parental consent), spending limit settings (daily and monthly limits, alert function, and emergency stop function), and usage history disclosure (reports for parents, spending details, and usage time records). The charges will be set in tiers, for example, a simple hint will cost 100 yen, a detailed map display 300 yen, and a 5-minute clairvoyance function 500 yen. In addition, monthly premium members will receive benefits such as unlimited hint use, exclusive strategy routes, and access to exclusive events. It will be made clear that a portion of the revenue from charges will be used to develop new maze courses and improve facilities, making it easier for visitors to understand. However, the basic functions provided for free will be enhanced so that visitors can fully enjoy the game without paying, and charges will be positioned as optional. For families, a parental control function will be implemented to prevent children from making charges without parental approval.

[0035] Barrier-free and physical support systems In at least one implementation, special considerations for visitors with mobility impairments or wheelchair users will be incorporated. Upon declaration at entry or prior reservation, barrier-free mode will be activated, and AI will prioritize guiding visitors along steps-free routes and wide corridors. The barrier-free system implements an accessibility evaluation database (detailed mapping of routes with a wheelchair-accessible width of 1.4m or more, a gradient of 1 / 12 or less, and steps of 2cm or less), dynamic route optimization (barrier-free route priority algorithm, detour distance minimization, and estimated travel time calculation), and assistive device integration (electric wheelchair control API, walking aid sensor integration, and prosthetic / orthotic adaptive control). The facility is wheelchair accessible and includes a wheelchair ramp (1 / 15 gradient, 1.8m wide, handrails on both sides, anti-slip surface), a lift (capacity 2 people + 1 wheelchair, lifting speed 15cm / second, 12 safety sensors), a wheelchair accessible toilet (compliant with JIS standards, ostomate-friendly, emergency call button), and a dedicated rest area (wheelchair parking available, charging facilities, blood pressure monitor and AED on-site). The walking assistance system includes routes for walker and cane users (non-slip flooring, appropriate handrail height of 75-85cm, rest benches spaced 50m apart), fatigue detection sensors (wearable device, walking pattern analysis, heart rate and blood oxygen saturation monitoring), and individual pace adjustment (1.5 times the normal time limit, mandatory rest suggestions, and companion pace synchronization). For visual and auditory support, we provide voice guidance systems (linked to tactile paving, directional sounds, obstacle voice warnings), tactile feedback (tactile displays, vibration pattern guidance, tactile maps), and sign language interpretation systems (AI sign language translation, real-time video display, sign language animation). For emergency response, we have specialist staff on hand (physical therapists, occupational therapists, sign language interpreters), medical equipment readily available (wheelchair-accessible stretchers, oxygen inhalers, blood glucose meters), and evacuation support protocols (wheelchair-accessible evacuation routes, dedicated evacuation vehicles, and coordination with welfare evacuation centers). In terms of the maze's physical structure, ramps are always installed along the main routes, ensuring a width (minimum 1.2 meters) that allows wheelchair access. Furthermore, more rest points are provided than usual for visitors using canes or walkers, with seating areas at appropriate intervals. These visitors are given longer time limits than usual, allowing them to enjoy the maze at their own pace. Additionally, the barrier-free routes are designed to offer the same level of puzzle-solving and entertainment as the regular routes, allowing visitors to enjoy the maze with companions. Emergency evacuation routes are also fully barrier-free, prioritizing safety above all else.

[0036] 360-degree video and immersive environment system In at least one embodiment, numerous displays are installed on the walls and ceilings of the maze, creating an immersive environment that surrounds visitors with 360-degree video. These displays can utilize a combination of various display technologies, such as LCD, LED, OLED, and projection, with the optimal one selected depending on the installation location and application. The 360-degree video system implements a high-density display arrangement (800 displays in total: 600 x 55-inch displays for walls, 150 x 32-inch displays for ceilings, and 50 x 46-inch waterproof displays for floors), an integrated control system (4K / 60fps video distribution, unified color temperature and brightness control, synchronization accuracy of ±1 frame), and an immersive content engine (360-degree video rendering, real-time viewpoint tracking, and parallax effect generation). To optimize display technology, indoor OLED displays (contrast ratio 1,000,000:1, DCI-P3 color gamut 100%, response time 0.1ms), outdoor LED displays (brightness 5,000cd / m², dustproof and waterproof IP65, operating temperature range -20℃ to +60℃), and projection mapping laser projectors (color purity 90% or higher, projection distance 0.5 to 30m, automatic distortion correction adjustment) are strategically placed for optimal use. Interactive functions integrate gesture recognition (Kinect v3, detection range 8m, skeletal recognition of 25 joint points, accuracy 95%), voice recognition (Amazon Alexa, Google Assistant, multi-language support, recognition rate in noisy conditions 85%), eye tracking (Tobii Eye Tracker, accuracy 0.4 degrees, sampling frequency 120Hz, calibration time 30 seconds), and facial recognition (Microsoft Cognitive Services, identification of 7 basic emotions, real-time processing). The content library includes natural environments (200 scenes such as forests, oceans, space, and seasonal changes), fantasy worlds (150 scenes such as magical forests, dragon caves, and sky castles), historical locations (100 scenes such as ancient ruins, medieval castles, and futuristic cities), and abstract spaces (250 scenes such as geometric patterns, light art, and musical visualization).The real-time generation system combines procedural generation algorithms (Perlin noise, L-system, fractal geometry), AI image generation (Stable Diffusion, DALL-E, Midjourney API integration), and physical simulations (fluid dynamics, particles, gravity effects). The display shows a variety of content, including virtual extensions of the maze, fantastical landscapes, character appearances, and hints. A dialogue system is also implemented where visitors can speak to the display, and the AI ​​character will understand their words using voice recognition technology and provide an appropriate response. For example, asking "What's ahead?" might elicit a mysterious reply such as "Only the brave can know," or provide concrete hints. The display resolution and content can be upgraded through system updates, ensuring that the experience always utilizes the latest video technology.

[0037] General-purpose AI system and technology integration platform In at least one embodiment, the AI ​​system has a general-purpose design that allows for the flexible integration of various types of artificial intelligence technologies. It utilizes the most suitable AI technologies selected and combined according to the purpose, such as machine learning, deep learning, reinforcement learning, natural language processing, and computer vision. The general-purpose AI platform incorporates a multi-algorithm framework (integrating TensorFlow, PyTorch, scikit-learn, XGBoost, and Apache Spark MLlib), an automated machine learning system (AutoML, hyperparameter optimization, automated model selection and evaluation, and a 90% reduction in execution time), and a distributed processing infrastructure (Kubernetes cluster, 20 GPU nodes, 80 NVIDIA A100s, and a total memory capacity of 10TB). For AI model management, it implements MLOps pipelines (MLflow, DVC, Kubeflow Pipelines), a version control system (Git LFS, model registry, and A / B testing functionality), and monitoring and alerting features (performance degradation detection, drift detection, and automatic retraining triggers). The processing method selection includes distribution based on response time requirements (edge ​​processing: within 50ms, fog processing: within 200ms, cloud processing: within 1 second), load balancing algorithms (round robin, weighting, minimum response time), and dynamic scaling (automatic scale-out when CPU usage exceeds 80%, scale-in after 10 minutes of low load). For natural language processing, it combines a large-scale language model (GPT-4, Claude, Gemini API integration, average response time of 800ms), a specialized domain model (specialized for tourism and entertainment, supports Japanese dialects, 100,000 technical term dictionaries), and a sentiment analysis engine (8 emotion categories, intensity scale of 0-100, accuracy of 92%). The computer vision system integrates object detection (YOLO v8, real-time processing at 60fps, detection accuracy of 95%), face recognition (FaceNet, 1 million registered faces in the database, recognition time of 100ms), behavior recognition (3D-CNN, classification of 24 basic behaviors, time series analysis), and anomaly detection (Isolation Forest, One-Class SVM, statistical outlier detection).The reinforcement learning features include an environment simulator (Unity ML-Agents, integrated physics engine, 1000 parallel environments), algorithm implementation (DQN, A3C, PPO, SAC, custom reward function design), and transfer learning capabilities (utilizing pre-trained policies, reducing new environment adaptation time by 80%). For example, machine learning is used to predict visitor behavior, natural language processing for voice interaction, and computer vision for facial recognition. Furthermore, AI processing can be performed using edge computing, fog computing, cloud computing, or a combination thereof, with the optimal configuration selected based on response time and processing load. AI models are regularly updated, and performance continuously improves through the addition of new algorithms and training data. The system also supports open-source AI frameworks, enabling the rapid adoption of the latest technologies developed by the community. This versatility ensures a sustainable system capable of handling future AI technologies.

[0038] Theme park integrated RPG system In at least one embodiment, the maze system includes an extension that transforms the entire theme park into an RPG. Data such as character levels, items, and achievements acquired in the maze can be used in other attractions within the theme park. The integrated RPG system implements a common profile management database (unique visitor ID, character status, item inventory, quest progress, achievement / title list), an inter-attraction linkage API (RESTful API, GraphQL, data synchronization protocol, real-time updates), and a unified storyline management system (20 main quest chapters, 100 side quests, 50 character-specific episodes, and 12 seasonal events). The leveling system implements an experience point calculation engine (base experience points, attraction-specific bonuses, cooperative play bonuses, time bonuses), level cap management (maximum level 100, exponential increase in experience points required for leveling up), and skill point allocation (6 ability scores, free allocation system, reset function). The item system includes a common currency "Park Coins" (obtained as a reward for clearing mazes, winning mini-games, and completing NPC quests), equipment management (weapons, armor, accessories, appearance change items), consumable items (healing items, buff items, skill enhancement items), and rare items (gacha system, drop rate 0.1-10%, exchange system). The quest system includes a dynamic quest generation AI (automatically generates the optimal quest based on visitor preferences, progress, and length of stay), multiplayer quests (2-8 player cooperation, role assignment, reward sharing), and hidden quests (unlocked by fulfilling specific conditions, rare rewards, 5 difficulty levels for discovery). Integration with other attractions provides features such as roller coasters (special effects for high-level players, 3D video customization, BGM selection), restaurants (level-specific menus, discount benefits, commemorative photos with chefs), and shops (member rank-specific benefits, early sales of limited goods, increased point redemption rates). For example, visitors who reach "Hero Level 5" in the maze can experience special effects on the roller coaster or order exclusive menu items at the restaurant. Each attraction is connected by a unified storyline, making visitors the protagonists of an epic adventure throughout the day. AI analyzes visitors' behavior history and dynamically generates quests and events tailored to individual preferences. Long-term story development spanning multiple visits is also possible, allowing visitors to continue from where they left off in their previous adventure. A theme park-specific virtual currency and point system are also introduced, allowing visitors to enjoy economic activity between attractions. This integrated system makes the entire theme park function as one giant RPG world, providing visitors with an unprecedented immersive experience.

[0039] High-density network of IoT sensors In at least one embodiment, IoT (Internet of Things) sensors are densely placed within the maze to collect and analyze detailed behavioral data of visitors. Various sensors, such as temperature sensors, humidity sensors, illuminance sensors, acoustic sensors, vibration sensors, and pressure sensors, constantly monitor environmental information. The IoT sensor network consists of a total of 5,000 smart sensors (2,000 environmental sensors, 1,500 motion sensors, 800 acoustic sensors, 500 vibration sensors, and 200 others), a mesh network (LoRaWAN, Zigbee 3.0, Thread, Wi-Fi HaLow, 100m communication range, automatic routing), and edge gateways (50 units deployed, ARM Cortex-A78 processor, 5G communication module, data preprocessing and compression functions). For environmental monitoring, the system includes a temperature and humidity sensor (accuracy ±0.1℃, ±1%RH, calibration cycle 6 months), an air quality sensor (CO2, PM2.5, VOC, NO2, O3 measurement, updated every minute), an illuminance sensor (measurement range 0.1~200,000 lux, color temperature measurement compatible), an acoustic sensor (frequency analysis 20Hz~20kHz, noise level, sound source direction detection), and a barometric pressure sensor (accuracy ±0.1hPa, weather change prediction). For human presence detection, the system integrates a PIR (pyroelectric infrared) sensor (detection angle 120 degrees, detection distance 10m, false detection rate less than 1%), a microwave sensor (utilizing the Doppler effect, movement speed detection, wall penetration detection), an ultrasonic sensor (distance measurement accuracy ±1cm, non-contact detection), and a pressure sensor (weight detection in 0.1kg units, foot pressure distribution analysis). The wearable connectivity includes Bluetooth 5.0 connectivity with smartwatches and fitness trackers (heart rate, steps, calories burned, blood oxygen saturation, stress level) and a dedicated wristband (accelerometer, gyroscope, GPS, body surface temperature), and data synchronization (1-second intervals, encrypted communication, privacy protection). Edge AI processing implements anomaly detection algorithms (Isolation Forest, LSTM Autoencoder, statistical outlier detection), real-time judgment (response within 100ms, automatic alert generation), and data compression (80% lossless compression rate, reduced bandwidth usage). Furthermore, biometric information such as heart rate, steps taken, and calories burned will be acquired from wearable devices worn by visitors (smartwatches, fitness trackers, dedicated wristbands, etc.). This data will be processed in real time by edge AI, and optimal environmental control will be performed according to the condition of each visitor. For example, the air conditioning will be automatically increased in areas where many visitors are feeling hot, and visitors who are exercising a lot will be suggested to take a break. The sensor data will be stored anonymized and will become valuable insights for future maze design and operational improvements. In addition, a safety management function will be implemented that uses an anomaly detection algorithm to detect problems such as visitors feeling unwell or getting lost at an early stage and notify staff.

[0040] Subscription / Membership System In at least one implementation, the maze system will adopt a subscription-based business model. Monthly members will enjoy various benefits, including unlimited access to the maze, priority access to new courses, participation in exclusive events, and in-app item grants. The subscription system will implement a tiered membership system (Bronze: ¥980 / month, Silver: ¥1,980 / month, Gold: ¥3,980 / month, Platinum: ¥9,800 / month), automatic billing management (credit card / debit card support, expiration prevention function, payment retry function), and a benefits management system (automatic granting of benefits based on membership rank, limited-time benefits, and cumulative benefit points). Member benefits will include access rights (Bronze: 10 times / month, Silver: 20 times / month, Gold: unlimited, Platinum: unlimited including family), priority access (7 days in advance for new courses, priority reservations for exclusive events, priority entry during peak hours), exclusive content (member-only puzzles, exclusive characters, exclusive BGM / sound effects), and discount benefits (10-30% discount on merchandise, 15% discount at restaurants, free parking). Member rank upgrades utilize a three-axis evaluation system based on usage frequency (monthly visits, duration of stay, activity participation), spending (monthly subscriptions, in-app purchases, related product purchases), and community contribution (review posting, social media sharing, friend referrals). Platinum members receive exclusive access to a private lounge (fully private room, dedicated concierge, premium tea and snack service), a personal AI guide (personalized AI, trained preference database, 24 / 7 support), and the right to create custom mazes (dedicated editor, 3D design tool, publishing and sharing functions). CRM integration includes customer data analysis (purchase behavior, preference analysis, churn prediction), personalized marketing (individual promotions, recommendations, retention strategies), and community features (member-only forums, offline events, fan club activities). Membership ranks are divided into Bronze, Silver, Gold, Platinum, etc., and members are promoted based on their usage frequency and spending. High-ranking members receive special services such as access to a private lounge, a personal AI guide, and the right to create customizable maze courses. In addition, a variety of pricing plans are available, including family membership plans and student discounts, to attract a wide range of visitors. Member data is managed with a CRM system, and promotions and new services tailored to individual preferences are suggested. Furthermore, community functions are provided for members to share strategy information and support the formation of a fan community through offline events. This subscription model aims to establish a stable revenue base and improve customer loyalty.

[0041] AR superimposed navigation and augmented reality systems In at least one embodiment, an overlay navigation system using AR (Augmented Reality) technology will be implemented. Visitors can view digital information superimposed onto the real-world maze space through AR glasses or their smartphone cameras. The AR overlay system implements high-precision position recognition technology (SLAM: Simultaneous Localization and Mapping, Visual-Inertial Odometry, positioning accuracy ±5cm, processing delay within 50ms), 3D object tracking (ORB-SLAM3, real-time feature point extraction and tracking, processing 1000 feature points per second), and device compatibility (ARKit-compatible iOS devices, ARCore-compatible Android devices, HoloLens 2, Magic Leap 2, dedicated AR glasses). The AR display system integrates a virtual object rendering engine (Unity 3D, Unreal Engine 4, real-time ray tracing, physically based rendering), occlusion processing (depth estimation, accurate display of context, Z-buffer optimization), and lighting integration (consistency with real-world lighting, shadow generation, reflection calculation). Interactive features include gesture recognition (25-point finger tracking, pinch, grab, and pointing operations), voice commands (50 types of commands such as "open the door" and "show hints," with 95% recognition accuracy), eye-tracking (eye tracking, gaze point selection, execution after 0.5 seconds of gazing), and touch operations (touch detection on virtual UI elements, haptic feedback). Content management features include seasonal theme switching (spring: cherry blossom effect, summer: marine life, autumn: autumn leaves, winter: snowflakes), event-linked features (Halloween: ghosts and bats, Christmas: reindeer and Santa Claus), personal settings (character selection, effect intensity adjustment, display language settings), and an update delivery system (OTA: Over-The-Air, automatic download, differential updates). Performance optimizations include the LOD (Level of Detail) system (adjusting rendering quality based on distance, stabilizing frame rate), frustration culling (excluding out-of-view objects, reducing rendering load by 60%), and dynamic texture compression (ASTC, ETC2, DXT5, reducing memory usage by 40%). For example, holding a smartphone over a wall might reveal a hidden door, or virtual footprints might appear on the floor to indicate the direction to go. AR characters can float through the maze, interacting with visitors and providing hints. AR can also depict effects that are physically impossible to achieve, such as ghosts passing through walls or magic circles floating in the air. Furthermore, AR effects can be easily changed according to the season or event, allowing for flexible operation, such as featuring ghosts for Halloween or Santa Claus for Christmas. AR technology allows for different visual experiences for each visitor, even in the same physical maze, providing fresh surprises even for repeat visitors.

[0042] VR fully immersive virtual maze system In at least one embodiment, a fully immersive maze experience using a VR (virtual reality) headset will be offered. Visitors will wear a high-resolution VR headset and explore a 360-degree virtual maze space. The VR immersion system integrates a high-performance VR headset (Varjo Aero, resolution 2880×1700 per eye, field of view 115 degrees, refresh rate 90 / 120Hz, IPD adjustment 58-72mm), a high-precision tracking system (SteamVR Lighthouse 2.0, tracking accuracy ±1mm, update frequency 1000Hz, maximum tracking range 10×10m), and a haptic feedback device (HaptX Gloves, haptic feedback at over 1000 points, force feedback 4lbf / finger, positional accuracy 0.1mm). The virtual environment is built using a physics engine (Unity Physics, Havok, NVIDIA PhysX, real-time collision detection and response), procedural generation (Perlin noise, Voronoi diagram, L-system, infinite variation generation), photorealistic rendering (ray tracing, global illumination, PBR materials), and spatial audio (Steam Audio, HRTF, distance attenuation and reverberation effects). To enhance immersion, it implements a natural movement system (Room-scale VR, teleportation movement, smooth movement, motion sickness reduction technology), physical constraint synchronization (collision prevention with real-world walls and obstacles, Guardian system, safety boundary display), and physiological comfort (automatic IPD adjustment, lens distance adjustment, diopter correction ±6D support). For multi-user support, the system implements network synchronization (UDP / TCP hybrid, latency compensation, position prediction), voice chat (3D positional voice, noise cancellation, real-time translation), cooperative play system (shared object manipulation, role assignment, progress synchronization), and avatar system (full-body tracking, facial expression synchronization, gesture recognition). Remote participation features include cloud rendering (NVIDIA GeForce Now, Google Stadia, latency under 100ms), streaming (H.265 encoding, 4K / 60fps, adaptive bitrate), and cross-platform support (PC VR, standalone VR, mobile VR, browser VR). The physical maze structure and virtual space are synchronized, allowing users to explore the VR world while actually walking through it. In the VR space, users can experience effects impossible in reality, such as rooms where gravity changes, corridors where spacetime is distorted, and gates guarded by giant dragons. By wearing gloves and vests with haptic feedback, the sensation of touching virtual objects is also reproduced. Remote participation is also possible; users can join the maze from home via a VR headset and enjoy cooperative play with on-site visitors. By utilizing VR technology, a grand world view that transcends budget and safety constraints is realized, providing visitors with an unforgettable experience.

[0043] Projection mapping dynamic video system In at least one embodiment, a dynamic video projection system using projection mapping technology is introduced to the walls and floor of the maze. High-brightness projectors project images that are synchronized with the movements of visitors onto the entire maze, which serves as a canvas. The projection mapping system is equipped with 80 high-brightness laser projectors (CHRISTIE D4K40-RGB, brightness 40,000lm, resolution 4096×2160, color gamut Rec.2020, laser life 20,000 hours) to cover a total projection area of ​​5,000 square meters. A 3D scanning system (FARO Focus Premium, measurement accuracy ±1mm, measurement range 350m, point cloud density 1 million points / square meter) accurately acquires the three-dimensional shape of the maze and automatically performs distortion correction of the projection surface. For real-time image processing, a GPU cluster (40 NVIDIA RTX A6000s, 1.92TB total VRAM, 240 TFLOPS rendering performance) and a dedicated video server (7thSense Delta Media Server, 4K x 16 output, frame synchronization accuracy ±1 frame) are deployed. For interactive detection, depth cameras (120 Microsoft Kinect Azure units, detection range 0.5~5.46m, depth accuracy ±11mm), LiDAR sensors (Velodyne VLP-16, 360-degree scan, measurement accuracy ±3cm, 300,000 points measured per second) and motion capture (OptiTrack, markerless tracking, accuracy ±0.1mm, latency 5ms) are integrated. The video effects library includes over 500 types of effects, including natural phenomenon simulations (fluid dynamics, particle systems, physics-based destruction effects), biomimetic animations (crowd simulations, plant growth algorithms, animal behavior AI), abstract artistic expressions (fractal generation, color fields, geometric transformations), and cultural motifs (Japanese patterns, Western styles, contemporary art, traditional craft patterns). Environmental synchronization features include weather data synchronization (rain → water droplet effect, strong winds → falling leaves, snow → snow crystal display), time synchronization (sunrise → morning glow effect, noon → strong sunlight effect, evening → sunset effect, night → starry sky projection), and sound synchronization (BGM beat synchronization, sound effect synchronization, reaction to audience applause and cheers). For example, interactive visual effects can be implemented, such as creating ripples on the floor when a visitor steps on a specific spot, or making vines grow when a visitor touches a wall. It is also possible to visually change the structure of the maze; images of walls collapsing or new passages appearing can make it seem as if the maze's layout has been altered without any physical modifications. The projection content can be changed according to the time of day or season, easily transforming the atmosphere from a bright forest during the day to an eerie cave at night. Projection mapping adds dynamic changes to a fixed physical structure, providing a maze experience where visitors can discover something new every time they visit.

[0044] 3D Hologram / Stereoscopic Image Projection System In at least one embodiment, a system is implemented that uses 3D hologram or stereoscopic projection technology to make virtual characters appear within a maze. Using special screens or fog screens, characters floating in the air are displayed to create an interactive experience with visitors. The 3D hologram system combines a volumetric display (Looking Glass Portrait, resolution 7680 x 4320, 45 viewpoints, 58-degree field of view, 150 cd / m² brightness), a Pepper's Ghost display (acrylic panel with 95% transparency, reflectivity control, and visibility adjustment depending on the viewing angle), and aerial imaging (parity mirror, hollow imaging, maximum real image size 2m x 2m x 2m). The fog screen projection employs an ultrasonic atomizer (particle size 1-10 μm, fog generation rate 0.1-3.0 L / min, duration 5 minutes in windless conditions), a high-speed projector (DLP technology, frame rate 240 fps, high-speed color wheel rotation), and a laser drawing system (RGB laser, drawing accuracy ±0.1 mm, vector drawing compatible). 3D character generation utilizes volumetric capture (360-degree shooting with 100 cameras, real-time 3D model generation, automated texture mapping), AI animation (motion synthesis, facial expression generation, lip-sync, natural motion interpolation), and real-time rendering (Unreal Engine, MetaHuman Creator, stable output at 60 frames per second). The dialogue system integrates a speech recognition engine (Google Speech-to-Text, Azure Cognitive Services, 98% recognition accuracy, 25 language support), natural language understanding (GPT-4, contextual understanding, sentiment analysis, intent estimation), speech synthesis (NVIDIA Omniverse Audio2Face, real-time lip-sync generation, 8 types of sentiment expressions), and gesture recognition (MediaPipe, 33 joint point detection, sign language recognition, cultural gesture support). For handling multiple visitors, it implements viewpoint-dependent display (visitor location tracking, individual viewpoint calculation, simultaneous support for up to 8 people), individual dialogue management (visitor identification, conversation history management, personalized responses), and group dialogue adjustment (speaking order management, promoting full participation, silence time adjustment). These holographic characters are controlled by AI and can answer visitors' questions, provide hints for solving puzzles, and sometimes surprise them. For example, it's possible to have an ancient sage appear to impart wisdom, or a fairy guide visitors. Holographic technology allows for a sense of presence, as if the characters were actually there, even though they are intangible. Viewpoint-dependent display technology is also used, allowing multiple visitors to interact with different characters simultaneously. This technology provides a richly narrative maze experience, inviting visitors into a fantastical world.

[0045] Vital Sign-Linked and Biomedical Information Adaptation System In at least one embodiment, a system will be introduced that measures visitors' vital signs in real time and adjusts the maze's design accordingly. Biometric information such as heart rate, skin electrical activity, and body temperature will be acquired using a smart ring, fitness tracker, or dedicated wearable device. The vital sign measurement system combines a multi-functional wearable device (Apple Watch Ultra, heart rate measurement accuracy ±2bpm, blood oxygen saturation measurement ±2%, skin temperature measurement ±0.1℃, waterproof performance 50m), a dedicated biosensor (Empatica E4, skin electrical activity measurement, accelerometer, infrared temperature sensor, Bluetooth 4.0 communication), and non-contact vital sign measurement (FotoPlethysmoGraphy, camera-based heart rate detection, 95% accuracy, measurement distance within 1.5m). The biometric data analysis system implements machine learning models (Random Forest, SVM, LSTM, 100-dimensional feature set, training data from 100,000 people), stress estimation algorithms (HRV: Heart Rate Variability analysis, RMSSD, pNN50 index, stress level quantification from 0-100), fatigue assessment (overall judgment from heart rate variability, skin electrical activity, and body movement), and emotional state estimation (classification into 5 states: excitement, relaxation, anxiety, joy, and fear, with an accuracy of 87%). The adaptive control system implements performance intensity adjustment (high excitement → calm performance, high stress → relaxing music, high fatigue → rest suggestion), environmental control (increased heart rate → decreased temperature, sweat detection → increased airflow, increased blood pressure → dimming lighting), and personal optimization (learning from past data, automatic threshold adjustment, outlier detection and exclusion). For group management, we implement group vitality analysis (calculation of average and variance for all members, outlier detection, majority-based decision-making), individual consideration balance (weighting of individual and group optimization, calculation of compromise points, maximization of everyone's satisfaction), and leader detection (influence analysis, decision-making pattern learning, group trend prediction). For privacy protection, we implement data anonymization (removal of personally identifiable information, statistical processing, k-anonymization k=5 or higher), consent management (opt-in / opt-out, clear statement of purpose of use, guarantee of the right to delete data), and security measures (encrypted communication AES-256, access control, log auditing). The AI ​​analyzes this data to estimate visitors' excitement levels, stress levels, and fatigue levels. Visitors with high excitement levels are provided with more stimulating experiences, while those with high stress levels are given lower difficulty levels or played relaxing music. If a group is participating, the AI ​​comprehensively assesses the vital signs of all members and creates a balanced experience that everyone can enjoy. This system provides a personalized maze experience optimized for each visitor's condition. The collected vital data is anonymized and used to verify and improve the effectiveness of the experiences.

[0046] Edutainment and STEM Education Integrated System In at least one implementation, an "edutainment" system integrating educational elements into the maze will be implemented. Various educational content, such as STEM (Science, Technology, Engineering, and Mathematics) education, history, geography, and language learning, will be incorporated into solving the maze puzzles. The STEM education system will include hands-on experimental equipment (spectrometer, pH meter, digital microscope, 3D printer, 20 types of programmable robots), a physics law experience zone (lever principle device, pendulum experiment, magnetism experience, electrical circuit assembly, fluid dynamics demonstration), and a chemistry experiment station (safe chemical reaction experiment, color change observation, crystal creation, acidity / alkalinity measurement). Programming education will include a visual programming environment (Scratch, Blockly, age-appropriate interface), physical computing (Arduino, Raspberry Pi, sensor / actuator integration), an introduction to AI / machine learning (Teachable Machine, data collection / learning / prediction experience), and robotics (LEGO Mindstorms, humanoid robot operation, autonomous control programming). The curriculum integration includes compliance with the National Curriculum Standards (science, mathematics, and technology subjects for elementary, junior high, and high school), automatic difficulty adjustment (grade-specific problem selection, comprehension measurement, provision of supplementary and advanced problems), an evaluation system (recording of correct answer rates, skill acquisition assessment, issuance of learning certificates), and teacher support (pre- and post-learning materials, evaluation reports, curriculum proposals). Multidisciplinary integrated learning combines history x science (recreation experiments of ancient technology, archaeology experiences, learning of inventions from different eras), geography x mathematics (map coordinate calculation, understanding of scale, statistical data analysis), and language x culture (multilingual programming, international communication, translation algorithm experience). Learning effectiveness is measured through pre- and post-tests (measurement of prior knowledge, confirmation of comprehension after learning, quantification of improvement), learning behavior analysis (trial and error patterns, concentration level measurement, cooperative behavior evaluation), and long-term follow-up surveys (confirmation of retention after 3 months and 1 year, sustained learning interest). For example, the system includes challenges that utilize physical laws (opening a door using the principle of leverage), simulations of chemical reactions (a path opens when the correct chemicals are mixed), and problems that require computational thinking (finding the shortest path by devising an algorithm). The difficulty level of the problems is automatically adjusted according to age and learning level, with basic content presented to elementary school students and more advanced content to middle and high school students. In addition, special programs aligned with the curriculum can be provided for group use by schools. Correct answers and learned content are recorded and provided as review materials at a later date. This educational system is expected to make learning fun and increase interest in learning.

[0047] Environmentally friendly and carbon-neutral operating system In at least one embodiment, environmentally conscious design and operational policies are fully adopted for the maze system. Sustainable materials such as recycled wood, recycled plastic, and bamboo are used for building materials to reduce waste. The environmentally conscious operational system implements renewable energy integration (1 MW of solar power, 500 kW of wind power, 200 kW of geothermal power, total annual power generation of 1.8 million kWh, 95% facility power self-sufficiency rate) and a carbon neutrality achievement plan (annual CO2 emissions of 500 tons, forest conservation project absorbs 600 tons of CO2, achieving a net negative 100 tons of CO2). Sustainable materials used include FSC-certified wood (no illegal logging, forest management certification, 100% traceability), recycled plastic (derived from PET bottles, 90% recycling rate, strength and weather resistance ensured), bamboo structure (growth rate three times faster than wood, lightweight and high strength, CO2 absorption of 35 tons per year), and biodegradable materials (PLA, biomass plastic, soil decomposition period of less than 6 months). The circular system implements rainwater recycling (collection area of ​​3,000 square meters, water treatment capacity of 200 cubic meters / day, 50% reduction in tap water usage), food waste recycling (composting, biogas fermentation, methane gas recovery and power generation), waste heat recovery (cogeneration, utilization of waste heat as hot water, 30% improvement in energy efficiency), and graywater treatment (reuse of washroom and handwashing wastewater, membrane separation treatment, compliance with water quality standards). Energy-saving control implements smart grid integration (optimization of power supply and demand, peak shifting, participation in demand response), IoT integrated management (integrated control of lighting, air conditioning and equipment, linked to usage areas, 80% reduction in standby power), and AI predictive control (linked to weather forecasts, visitor number prediction, energy usage optimization). The environmental education program includes visualization of CO2 reduction effects (real-time display, individual contribution calculation, annual reduction calculation), ecosystem learning (biotope observation, insect and plant surveys, understanding of biodiversity), recycling and craft activities (upcycling of waste materials, creative activities, raising environmental awareness), and carbon footprint calculation (measuring the impact of transportation and food choices, promoting behavioral change). Third-party certifications obtained include LEED certification (building environmental performance, platinum level), ISO 14001 (environmental management system, continuous improvement), and carbon neutrality certification (third-party verification, compliance with international standards). All lighting will be energy-saving types such as LEDs or OLEDs, and will only turn on when necessary in conjunction with motion sensors. Solar panels will be installed on the roof and walls to generate some of the electricity needed to operate the maze. Rainwater will be collected in storage tanks and reused for flushing toilets and watering plants. In addition, an environmental education corner will be set up inside the maze, where visitors can learn about the SDGs (Sustainable Development Goals) in an enjoyable way. For example, there will be a quiz about waste sorting and exhibits where visitors can experience how renewable energy works. Furthermore, the latest environmental technologies will be actively introduced, such as flooring that generates electricity from visitors' movement and special paint that absorbs CO2.

[0048] eSports and Competitive Gaming Integrated System In at least one embodiment, the maze system will incorporate esports elements to enhance its competitiveness. Various competition formats will be available, including time attack mode, score attack mode, and battle royale mode. The esports system will be equipped with high-precision measurement equipment (laser timer accuracy ±0.001 seconds, position tracking accuracy ±1 cm, motion analysis 30 fps, reaction time measurement ±1 ms), a dedicated competition course (standardized difficulty, fairness ensured, spectator area provided, commentary booths provided), and a live streaming system (4K HDR streaming, multi-angle video, real-time commentary, accommodating 1 million viewers). The competition modes will include individual time attack (setting time limits, shortest route competition, penalty system), team cooperative play (2-4 person teams, role assignment, coordination evaluation), battle royale (16 players simultaneously, elimination system, until only one person remains), and endurance (endurance measurement, long play time, physical fitness and concentration evaluation). For professional competitions, we have established official rules (certified by the International Esports Federation, unified anti-doping rules and equipment regulations), a refereeing system (AI automated judging, human referee support, appeal function), a ranking system (world unified rating, seasonal rankings, lifetime performance management), and a prize money and awards system (total of 100 million yen / year, 10 million yen prize money for the winner, sponsor support). For the viewing system, we offer real-time commentary (AI commentary, professional gamer commentary, multilingual support), audience participation (prediction voting, cheering system, interactive viewing), VIP viewing seats (premium seats, player point-of-view video, data analysis screen), and online viewing (Twitch, YouTube® streaming, chat function, tipping system). For player development, we have established a practice mode (weakness analysis, intensive training, AI coaching), training facilities (dedicated practice space, coach dispatch, mental training), a scholarship system (support for young players, tuition assistance, support for turning professional), and a player database (performance analysis, scouting, transfer market). Participants' scores are displayed in real time on a ranking board, allowing them to compete with players from around the world. Official tournaments are held regularly, with prize money and rewards awarded to top finishers. Events such as demonstrations by professional players and strategy workshops are also held. The mazes used for competition are set to a higher difficulty level than the regular version, testing reflexes, judgment, and strategic thinking. A spectator mode is also available, allowing players to watch other players' challenges on a large screen and enjoy them with live commentary. This esports transformation is expected to evolve the maze from a mere attraction into a competitive venue, attracting a new customer base and increasing media exposure.

[0049] Multisensory stimulation and five-sense experience integrated system In at least one embodiment, a multisensory stimulation system is introduced within the maze to provide a comprehensive experience that includes not only sight and hearing, but also touch, smell, temperature, and other senses. The flooring has different textures depending on the location (sand, grass, stone, water, etc.), providing hints about the current location through the feel of walking. The multisensory stimulation system integrates a tactile floor system (20 types of textured flooring, electrically adjustable hardness, temperature control ±5℃, vibration feedback 0.1-200Hz), an olfactory experience device (200 aroma diffusers, 100 types of fragrance components, diffusion control radius 3m, concentration adjustment 0.1-10ppm), and a taste experience station (safe food samples, identification of 5 basic tastes, tasting of local specialties, and allergy-friendly options). For temperature and humidity control, the system implements local environmental control (area-specific temperature settings 15-35℃, humidity 30-80%RH, wind speed 0.1-3.0m / s), perceived temperature adjustment (Peltier element, radiant heating and cooling, airflow control), and a seasonal reproduction system (spring breeze experience, summer heat, autumn coolness, winter cold). For tactile feedback, it employs haptic technology (ultrasonic touch, vibration touch, electrical stimulation, magnetic touch), texture simulation (material feel reproduction, hardness / roughness expression, friction force change), and aerial touch (non-contact touch, 3D space touch sensation, Ultrahaptics technology). For the acoustic and vibration system, it implements 3D spatial sound (object-based audio, 22.2ch surround, binaural recording and playback), vibration effects (underfloor vibration device, wall vibration speaker, perceived vibration 0.1-200Hz), and ultrasonic touch (focused ultrasound, local touch sensation generation, safety ensured at 20kHz or less). The synchronization control system incorporates a five-senses integrated AI (interaction model between senses, optimal timing calculation, individual sensitivity adaptation), scenario management (time-series performance control, visitor behavior linkage, situation-adaptive adjustment), and biological response monitoring (pleasure / discomfort determination, overstimulation detection, automatic adjustment function). Safety management includes allergy countermeasures (pre-declaration system, ingredient labeling, emergency response protocol), stimulation intensity limiting (compliant with WHO standards, individual settings, consideration for children and the elderly), and medical monitoring (on-site nurses, AED placement, emergency contact system). The system works in conjunction with the air conditioning system to change temperature and humidity in specific areas, recreating environments such as deserts, jungles, and snow-capped mountains. Aroma diffusers release scents of forests, the sea, and flowers at appropriate times. Vibration devices are incorporated into the walls to provide tactile feedback during earthquake and explosion simulations. Ultrasonic speakers enable audio guidance that can only be heard at specific locations. Through these multi-sensory stimuli, visitors can experience the maze's world with their whole bodies, leaving a strong and memorable impression.

[0050] Metaverse Integration Hybrid Experience System In at least one embodiment, the maze system interacts with the metaverse space, providing an experience where the physical maze and digital space seamlessly merge. Visitors explore the real-world maze while simultaneously controlling avatars in the metaverse, cooperating in both worlds to solve puzzles. The metaverse integration system includes a virtual space platform (Unity Netcode, Photon Engine, 10,000 simultaneous connections, response time within 50ms), a 3D virtual maze (complete digital replica of the physical maze, additional virtual areas, zero gravity space, spacetime warp), and an avatar system (full body tracking, facial expression synchronization, voice conversion, personality customization). For reality-virtual integration, a location synchronization system (GPS, UWB, SLAM technology, position accuracy ±10cm, latency compensation function), state sharing (item acquisition, puzzle progress, experience history, real-time synchronization), and cross-reality communication (real participants ⇔ virtual participants, voice, text, and gesture communication) are implemented. The digital economic system incorporates NFT items (limited items, proof of ownership, secondary market, royalty setting), cryptocurrency (Parkcoin, blockchain management, payment / remittance functions, fiat currency pegging), and virtual real estate (lots in virtual space, rights trading, customization rights, monetization functions). For global participation, it implements multilingual support (real-time translation in 25 languages, cultural considerations, regional events), time zone support (24-hour operation, regional peak adjustment, event time optimization), and low-latency communication (CDN utilization, edge servers, regional optimization). For AR / VR integration, it enables Mixed Reality support (HoloLens, Magic Leap, coexistence of real and virtual objects), haptic feedback (unified physical and virtual touch, force feedback, temperature / vibration synchronization), and world-scale experience (real-world size ⇔ virtual size conversion, viewpoint switching, shared spatial awareness). The monetization model includes virtual merchandise sales (avatar outfits, digital souvenirs, limited items), advertising and sponsorships (virtual billboards, corporate events, product placements), and premium experiences (VIP areas, exclusive content, priority access). For example, a system could be implemented where entering a code found in the real world into the metaverse opens up new paths. Friends in remote locations can also participate from the metaverse and enjoy cooperative gameplay with on-site visitors. Furthermore, items and points acquired in the metaverse can be used in the real-world maze, and vice versa. It is also possible to issue certificates of maze completion and exclusive items as digital assets by utilizing NFT (Non-Fungible Token) technology. This metaverse integration will realize a new form of entertainment that transcends physical limitations and enable the construction of a global customer base.

[0051] IoT-enabled wearable smart shoe system In at least one embodiment, an advanced guidance system using IoT-enabled wearable devices will be implemented. Specifically, by having visitors wear smart shoes (e.g., FUMM shoes) with built-in color and pressure sensors, the system will sense the color and texture of the flooring and provide guidance and visual effects accordingly. The smart shoe system integrates multi-functional sensors (RGB color sensor, pressure sensor 0.1-200kg, temperature sensor, vibration sensor, GPS, 9-axis IMU), wireless communication functions (Bluetooth 5.2, Wi-Fi 6, LoRaWAN, communication range 100m), and a battery system (wireless charging compatible, 24 hours of continuous use, 80% in 30 minutes of fast charging). For floor sensing, the system implements color matching (RGB value acquisition, color temperature measurement, pattern recognition, 98% accuracy), material identification (pressure and vibration pattern analysis, discrimination of 20 types of materials, accuracy improvement through machine learning), and location determination (indoor positioning accuracy ±30cm, step counting, movement trajectory recording). Interactive control features include gait pattern detection (10 types including normal walking, jogging, jumping, dancing, and skipping), foot pressure distribution analysis (center of gravity shift, balance assessment, fatigue level determination), and gesture recognition (foot taps, step patterns, direction indications, Morse code input). The feedback system provides vibration patterns (direction indications, warnings, success notifications, 10 patterns), LED display (sole and side LEDs, RGB control, brightness adjustment, pattern display), and acoustic feedback (built-in speaker, bone conduction, personalized voice, ambient noise compatibility). Gamification elements include step challenges (step count goals, calorie consumption calculation, health promotion), dance games (rhythm games, step pattern judgment, score evaluation), and treasure hunt games (hidden area discovery, specific color / pattern search, reward acquisition). Health management functions include gait analysis (stride length, walking speed, sole pressure distribution, posture assessment), fatigue level assessment (gait pattern changes, balance deterioration, rest recommendations), and fall prevention (balance abnormality detection, fall risk assessment, prevention alerts). For example, stepping on a red floor triggers a warning sound indicating danger, while stepping on a blue floor plays soothing music indicating the correct path. For children, there's also a system where stepping on floors of a specific color in a particular order starts the game. The system also detects actions such as jumping and running, and activates mechanisms within the maze accordingly. Steps and distance traveled are recorded, and reward points are awarded based on the amount of exercise. Information from the wearable device is synchronized in real time with a smartphone app, and feedback is also provided through vibration and sound. This technology enables a full-body interactive maze experience and contributes to promoting physical activity, especially among children.

[0052] Dynamic lighting and light show integrated system In at least one embodiment, a dynamic lighting system is introduced within the maze, utilizing LED lighting and laser beams for special effects. Thousands of RGB LEDs are placed throughout the maze, generating complex light patterns through individual control. The dynamic lighting system incorporates a high-density LED layout (50,000 LEDs in total, RGB + white LEDs, individually addressable, dimming range 0.01-100%, variable color temperature 1800K-6500K), a DMX512 control system (512 channels x 100 universes, update frequency 44Hz, synchronization accuracy ±1ms), and laser effects equipment (30 x 20W RGB lasers, safety class 3R, variable beam diameter, pattern drawing capability). The light control engine implements real-time rendering (GPU acceleration, frame rate 60fps, latency less than 10ms), physically based lighting (ray tracing, global illumination, shadow and reflection calculation), and AI-generated patterns (GAN-based light pattern generation, music synchronization, 8 types of emotional expression). Interactive control features motion detection (visitor tracking, movement prediction, proactive lighting), voice response (frequency analysis, beat detection, real-time music synchronization), touch / gesture synchronization (wall touch detection, aerial gestures, light trail display), and biometric information synchronization (heart rate synchronization, stress level-dependent color, brightness adjustment based on fatigue). The performance programs include reproductions of natural phenomena (lightning effects, aurora, flame flickering, water surface reflection, sunlight filtering through forest trees), abstract expressions (geometric patterns, fractals, color fields, moiré effects), narrative performances (character appearances, magic effects, battle scenes, emotional moments), and seasonal / time-based performances (sunrise, sunset, starry sky, snowscape, cherry blossom blizzard). The music synchronization function includes BPM analysis (automatic song tempo detection, time signature recognition, phrase segmentation), frequency analysis (separation of low, mid, and high frequencies, instrument separation, timbre recognition), emotion analysis (evaluation of song's emotional value, evaluation on four axes: brightness / darkness, intensity / calmness), and automatic choreography (music structure analysis, build-up prediction, climax production).Energy efficiency improvements include enhanced LED efficiency (luminous efficiency of 150 lm / W, thermal management system, 50,000-hour lifespan), dimming control (lights on only when needed, linked to motion sensors, 70% reduction in power consumption), and scheduling (brightness adjustment by time of day, energy-saving mode, maintenance time setting). The lighting's color temperature, brightness, and flashing patterns change according to the visitor's progress. For example, as they approach the goal, the lighting shifts from warm to cool colors, or the flashing speed increases. Specific actions can trigger a path of light to appear on the floor, indicating the next destination. Light shows perfectly synchronized with music are also implemented, creating an immersive experience reminiscent of a concert venue. Laser beams are combined with mist and smoke to create three-dimensional walls of light, functioning as virtual obstacles. Furthermore, wearable LEDs worn by visitors are synchronized, creating a visual sense of unity, such as having team members light up in the same color during team competitions.

[0053] 3D Sound and Spatial Acoustic System In at least one embodiment, a state-of-the-art 3D sound system provides a highly immersive acoustic experience. Hundreds of directional speakers are placed throughout the maze, tracking each visitor's location in real time and delivering individually optimized sound. The 3D spatial sound system consists of a directional speaker array (400 units, frequency response 20Hz-40kHz, directivity angle ±15 degrees, maximum sound pressure 120dB), an ultrasonic acoustic beam (40kHz modulation, audible range downconversion, beam width 30cm, range 10m), and object-based audio (Dolby Atmos, 22.2ch compatible, simultaneous playback of 128 audio objects). For spatial audio processing, we have implemented HRTF (Head-Related Transfer Function) personalization (auricle shape measurement, individual acoustic characteristics, 30% improvement in directional localization accuracy), binaural synthesis (real-time convolution, GPU acceleration processing, latency within 2ms), ambisonics (third-order ambisonics, spherical harmonics, 360-degree sound field reproduction), and wavefield synthesis (2.5-dimensional sound field reproduction, virtual sound source placement, expression of distance and movement). For real-time sound field control, we have implemented a sound source tracking system (sound source localization, movement prediction, Doppler effect, reflected sound calculation), an acoustic rendering engine (physically based acoustics, reflectivity by material, variable reverberation time 0.5-8 seconds), and adaptive acoustic control (adaptation to ambient noise, consideration of auditory masking, support for individual hearing characteristics). The ultrasonic technology applications include parametric speakers (self-demodulation, high directivity, acoustic spotlight effect), ultrasonic haptics (non-contact tactile generation, airborne touch feedback), and airborne display synchronization (hologram sound source, 3D video / audio integration, positional accuracy ±1cm). Individual audio delivery includes auditory profiles (age-specific hearing characteristics, music preferences, volume settings, language settings), personalized audio (personalized EQ, hearing correction, preferred sound quality adjustment), and privacy protection (personalized audio, inaudible to others, information leakage prevention).The sound effects library includes 200 types of natural sounds (birdsong, wind, water, insect sounds, thunder, etc.), 300 types of artificial sounds (machine sounds, warning sounds, musical instrument sounds, sound effects, etc.), 150 types of ambient sounds (city sounds, forest sounds, coastal sounds, cave sounds, etc.), and sci-fi sound effects (space sounds, magic sounds, robot sounds, futuristic sounds, etc.). For example, it can recreate a three-dimensional sound field, such as hearing enemy footsteps from the right or the sound of birds flying overhead. Using ultrasonic acoustic beam technology, it is also possible to deliver secret messages that can only be heard in specific locations. Furthermore, by utilizing binaural recording technology, visitors wearing headphones can enjoy a more precise 3D sound experience. Vibration speakers are embedded in the floor, allowing visitors to realistically experience effects such as earthquakes and explosions through vibrations transmitted from their feet. Ambient sounds, sound effects, music, and narration are seamlessly blended, completely immersing visitors in a world of sound.

[0054] Live performers and animatronic character systems In at least one implementation, a character guide system using live performers will be introduced. Professional actors and entertainers will roam the maze dressed as characters from a fantasy world, engaging in impromptu conversations and performances with visitors. The performer system will include professional performers (10 actors, 5 dancers, 3 magicians, 2 acrobats, all with over 5 years of acting experience), a character setting database (50 original characters, detailed backstories, personality settings, speech patterns and gestures), and costumes and special effects makeup (Hollywood-level special effects makeup, silicone masks, full body suits, and LED-embedded costumes). The animatronics integration will include high-precision robot characters (Disney Imagineering technology, 32-axis control, 16 facial muscle patterns, natural blinking and lip-syncing), an AI control system (voice recognition, natural language processing, emotion detection, and appropriate response selection), and remote control capabilities (precise operation from a distance, VR control system, and controllers with haptic feedback). Performance management includes performance scheduling (character placement by time slot, linked to crowd conditions, fatigue management), an improvisation scenario database (over 1000 scene settings, tailored to visitor attributes, cultural considerations), and safety management (performer location tracking, emergency communication, medical support system). Visitor interaction includes the use of personal information (calling out names, birthday celebrations, repeat visitor recognition, preference memory), group support (family structure recognition, age group adaptation, all-participation performances), and photo / video shooting (professional photographer accompaniment, Instagrammable poses, AR effect additions). Technology integration includes AR / VR integration (augmented reality effects, hologram synthesis, virtual costumes and props), IoT integration (environmental control, lighting / sound synchronization, special effect triggers), and AI support (dialogue suggestion, situation judgment support, optimal timing notification). Quality control includes maintaining performance levels (regular training, feedback collection, skills evaluation, and improvement guidance), customer satisfaction surveys (evaluation system, collection of improvement requests, individual performer evaluations, and compensation-linked evaluations), and cultural adaptation (multilingual support, religious considerations, understanding of local customs, and development of international awareness). These characters are not merely guides, but are important figures deeply involved in the world of the maze. For example, the sage character conveys clues to solving the puzzles in poetic language, while the jester character misleads visitors with false information. There are also mechanical characters using the latest animatronics technology, performing movements and transformations impossible for humans. These characters work in conjunction with AI, appearing at the optimal time and providing personalized performances based on the visitor's behavior history and current progress. Character shows are also held regularly, where multiple characters cooperate to unfold an epic story.

[0055] Stamp rally and trading card integrated system In at least one embodiment, a collectible game system combining stamp rally and trading card elements will be implemented. Multiple stamp stations will be placed within the maze, and players can get a stamp on a special sheet by correctly answering the quiz presented at each station. The stamp rally system will incorporate digital and analog integration (20 physical stamp locations, QR code® reading, NFC touch, GPS location confirmation, dedicated app linkage), a question database (2000 questions in total, 5 difficulty levels, automatic selection by age, correct answer rate adjustment function), and a card gacha system (5 physical gacha machines, digital gacha, drop rate adjustment, rarity management). The card design will include original artwork (created by a professional illustrator, 100 characters, 50 backgrounds, 30 special effects), rarity settings (common 60%, rare 25%, super rare 10%, ultra rare 4%, legend 1%), and functional cards (AR display, hologram, sound playback, scent, temperature change). The collection elements include series management (seasonal, event-limited, collaboration cards, commemorative cards), completion rewards (special benefits for collecting all types, limited goods, VIP experience rights), and an exchange system (card exchange between visitors, official exchange events, automatic rate calculation). The game elements include a card battle system (turn-based strategy game, attribute compatibility, skill effects, victory rewards), deck building (40-card limit, cost management, synergy effects, tactical diversity), and a tournament system (monthly tournaments, season-based, world championships, prize money system). Digital integration includes an in-app card encyclopedia (collection rate display, detailed information, 3D display, evolution system), NFT integration (blockchain certification, ownership protection, secondary market, value preservation), and SNS integration (show off collections, post rare cards, exchange requests, sharing strategy information). The educational value promotes knowledge learning (history, science, culture, language learning), strategic thinking (improvement of logical thinking, planning, judgment, and creativity), and social development (exchange negotiation, cooperative play, fair play spirit, international exchange). Collect all the stamps and bring them to the reception desk to receive a gold coin (for all correct answers) or a silver coin (for some correct answers) depending on the number of correct answers. These coins can be used in special gacha machines and card game machines to obtain character cards of different rarities. The cards depict characters encountered in the maze, original monsters, and more, and digital versions can also be obtained by scanning the QR code (registered trademark). New card series are added regularly, and seasonal and collaboration cards are also issued. Card battle tournaments are also held, allowing players to enjoy competitive games using their collected cards.

[0056] Freemium / tiered billing system At least one implementation will adopt a freemium business model, where a basic experience is offered for free or at a low price, while revenue is generated through value-added services. The basic admission fee includes exploring the main route, solving standard puzzles, and basic presentation. The freemium revenue system will implement tiered services (Free: basic experience only, Light: ¥480 / month, Standard: ¥980 / month, Premium: ¥1980 / month), dynamic pricing (supply and demand analysis, competitor pricing research, customer willingness to pay survey, automatic optimal pricing), and personalized recommendations (analysis of individual usage patterns, optimal plan recommendations, upgrade suggestions, and churn prevention offers). The game will manage three types of in-game currency: free "Adventure Points" (earned by solving mazes, winning mini-games, and referring friends), paid "Premium Gems" (purchased, used for high-value rewards and limited item exchanges), and time-limited "Event Coins" (used for limited-time events, special rewards, and rarity presentations). The paid items include convenience enhancements (hint purchases, time limit extensions, warp function, priority entry), experience enhancements (hidden areas, exclusive characters, special effects, VIP treatment), appearance customization (avatar outfits, accessories, effects, theme changes), and social functions (team creation, private rooms, messaging function, gift sending). For revenue optimization, we conduct A / B testing (pricing, UI design, offer content, timing optimization), cohort analysis (generational purchasing behavior, retention rate analysis, LTV prediction, churn prevention measures), and behavioral data analysis (pre-purchase behavior patterns, purchase decision factors, satisfaction correlation, repeat purchase factors). Customer support includes tiered support (free users: FAQ / chatbot, paid users: email / phone, premium: dedicated representative / priority support), problem solving (technical trouble resolution, billing trouble resolution, account recovery, data migration support), and satisfaction improvement (regular surveys, collection of improvement requests, early access to new features, invitations to exclusive events). On the other hand, premium options include additional hidden routes, high-difficulty puzzle challenges, exclusive AR content, priority entry, and limited-edition merchandise. A game currency system will also be introduced, with two types of currency: one that can be earned for free through activities within the maze, and another that can be purchased with real money. These currencies can be used to purchase hints, rent special equipment, and access exclusive areas. A monthly subscription plan is also available, offering benefits such as unlimited access to all premium content, access to a dedicated lounge, and priority participation in events.

[0057] As at least one implementation, a special maze experience will be offered to fans through collaboration with popular IP (intellectual property). A limited-time maze will be constructed that faithfully recreates the world of the anime, movie, game, manga, etc. For example, in a collaboration with a popular anime, buildings and landscapes from the work will be recreated within the maze, and life-sized figures of characters and audio guides by voice actors will be introduced. Visitors can immerse themselves in the role of the main character and relive famous scenes from the work, or challenge themselves to solve puzzles in an original story. A collaboration-exclusive costume rental service will also be offered, allowing visitors to enjoy the maze while cosplaying as a character. Furthermore, those who complete the maze will be given the right to participate in a lottery to win limited-edition goods featuring newly drawn illustrations or goods signed by voice actors. These collaborations will be changed regularly to constantly attract new fan bases. In implementing IP collaborations, detailed production plans will be formulated through close consultation with copyright holders to ensure that the world view of the original work is not compromised. The sound effects within the maze will use music arranged from the original work's background music, and the lighting effects will also be adjusted to match the atmosphere of the work. For example, in collaborations with dark fantasy works, dim lighting and heavy music will create a sense of tension, while in lighthearted comedy works, colorful lighting and cheerful background music will create a fun atmosphere. Furthermore, AR goggles will be used to allow actual characters to guide visitors through the maze and interact with them. Sales of related merchandise will also be enhanced during the collaboration period, with limited-edition goods linked to the maze experience and collector's items that come with a certificate of experience. Social media integration will allow for easy sharing of commemorative photos with characters and the experience itself, ensuring buzz within the fan community. These comprehensive efforts will provide an immersive experience that exceeds the expectations of IP fans, guaranteeing the success of the collaboration.

[0058] At least one implementation involves a corporate service specifically designed for corporate training and team building. The entire maze, or a portion thereof, is rented out, and a customized program tailored to the company's needs is implemented. For example, in training aimed at improving communication, team members start from separate locations and work together to reach a meeting point while sharing information. Leadership training provides participants with the experience of taking turns leading a team. Puzzle-solving activities simulating business situations are also included to improve problem-solving skills. After the training, a report analyzing each participant's behavioral data is provided, visualizing their strengths and areas for improvement. Furthermore, videos of the training and certificates documenting the team's success are issued. For regular users, a service to develop unique maze courses is also offered, allowing for the creation of completely original training programs that reflect the company's culture and values. In the corporate service, a professional facilitator provides comprehensive support, from program design and implementation to follow-up, tailored to the company's specific challenges and goals. Before the training, AI proposes optimal team formations and task settings based on information such as participants' job titles, departments, and skill levels. Within the maze, each team's progress is monitored in real time, and facilitators intervene to provide support as needed. For example, teams with communication challenges are given additional tasks to facilitate dialogue, and teams lacking decisiveness are given time-limited decision-making tasks. Training data is analyzed in conjunction with organizational diagnostic tools and used to visualize team dynamics, understand individual behavioral characteristics, and clarify communication patterns across the organization. Furthermore, to enhance the sustainability of the training's effects, regular follow-up sessions are conducted after the maze experience to support the application of what has been learned to practical work. Through these comprehensive services, we provide a highly effective talent development program that goes beyond mere recreation.

[0059] In at least one embodiment, a learning maze system linked to programming education will be implemented. Programming stations will be set up in specific areas of the maze, allowing visitors to control the maze's mechanisms by writing simple code. For example, they can use a block-based visual programming language to create sequences to open doors or operate robots to clear paths. Depending on age, users can choose from simple Scratch-like interfaces to more advanced programming languages ​​such as Python. Elements of physical computing, combining sensors and actuators, will also be introduced, providing the experience of operating actual machines. Special routes that can be unlocked by successful programming and a challenge mode to compete on code efficiency will also be available. For schools, special programs aligned with information education curricula will be offered, allowing students to develop computational thinking while having fun. The programming learning system features a meticulously designed step-by-step learning curriculum, providing appropriate challenges for each level, from beginner to advanced. Beginner levels start with simple sequential processing (forward, turn, stop), while intermediate levels teach complex motion control using conditional branching (if statements) and loops. At the advanced level, participants will be challenged to implement sophisticated algorithms that integrate data from multiple sensors and create adaptive control programs that incorporate fundamental machine learning concepts. Each station will have experienced mentors who will answer visitors' questions in real time. Furthermore, created programs will be automatically evaluated, providing detailed feedback on aspects such as execution speed, memory usage, and code readability. Outstanding programs will be displayed in the "Code Gallery" and shared for the benefit of other visitors. In addition, programming contests will be held regularly, with special rewards and certificates awarded to programmers who solve specific challenges most efficiently. These educational elements create a new form of educational experience that blends entertainment and learning.

[0060] At least one implementation will include a "sensory-friendly" mode that takes into account sensory sensitivities and developmental characteristics. This mode is designed to minimize light and sound stimuli, allowing visitors to enjoy the maze in a calm environment. Lighting will consist only of soft, indirect light, avoiding sudden changes in brightness. Sound will consist only of calming background music, primarily ambient sounds, avoiding sudden loud noises or high-frequency sounds. A social story detailing the maze's content will be provided beforehand, allowing visitors to anticipate what will happen. More rest areas will be provided than usual, and a cool-down room will also be available. Furthermore, tools to adjust sensory stimulation (noise-canceling headphones, sunglasses, weighted vests, etc.) will be available for free rental. Staff will be trained on developmental disabilities and sensory sensitivities, ensuring they can provide appropriate support. This mode will be available at specific times and will also be available by individual reservation. The implementation of the sensory-friendly mode will involve scientifically-based environmental design in collaboration with medical professionals, occupational therapists, and special education specialists. The color scheme within the maze has also been carefully considered, using neutral colors as the base and avoiding high-contrast color combinations. Special materials that absorb footsteps are used for the flooring, and sound-absorbing materials are placed on the walls to mitigate acoustics. In addition, a system is in place to register each visitor's sensory profile in advance, and the environment within the maze is automatically adjusted according to individual needs such as photosensitivity, sound sensitivity, and tactile sensitivity. For example, when a visitor with photosensitivity approaches, the lighting in that area is automatically dimmed, and for visitors with sound sensitivity, the surrounding volume is automatically adjusted. Furthermore, guidelines for companions are provided, detailing appropriate support methods and emergency response procedures. Feedback from individuals with disabilities and their families is collected regularly to ensure continuous improvement. Through these comprehensive considerations, an inclusive environment is created that all visitors can enjoy with peace of mind.

[0061] (Omitted due to lack of diagrams)

[0062] As at least one implementation, an AI-based dynamic pricing system will be introduced. Demand forecasts will be made by comprehensively analyzing past visitor data, weather information, nearby event information, and social media trend analysis. Based on this forecast, admission fees will be automatically adjusted on an hourly basis. For example, during peak hours such as sunny weekend afternoons, the fee will be set at 1.5 times the normal rate, while during off-peak hours such as rainy weekday mornings, the fee will be set at 0.7 times the normal rate. Price changes can be checked in real time via a dedicated app or website, and it is also possible to fix the price with advance reservations. Various pricing plans will also be available, including last-minute booking discounts, early morning discounts, and late-night discounts. Furthermore, customers who visit during off-peak hours will be offered incentives such as discount coupons for future use or gifts of limited-edition merchandise. This system will simultaneously achieve crowd leveling and revenue maximization. As the dynamic pricing system becomes more sophisticated, more personalized pricing will be possible, taking into account individual attributes and past usage history. For example, loyalty discounts are automatically applied to frequent visitors, and special rates are offered to first-time visitors to encourage them to experience the facility. Segment-specific optimizations are also implemented, such as additional discounts for children for families and expanded student discounts for students. The AI ​​integrates and analyzes external data, including competitor pricing trends, local event calendars, and transportation status, to achieve more accurate demand forecasts. Furthermore, to ensure transparency in pricing fluctuations, the app displays a forecast price graph for the next week, allowing visitors to choose the most convenient time to visit. For businesses, fixed-rate plans with annual contracts are available to support stable usage. Integration with revenue management systems enables real-time sales analysis and pricing optimization, contributing to increased operational efficiency. These advanced pricing strategies achieve both visitor satisfaction and business profitability.

[0063] In at least one implementation, a surprise performance system featuring unexpected acts will be implemented. Professional actors, dancers, magicians, acrobats, etc., will suddenly appear in the maze without prior notice, surprising visitors. These performers are portrayed as inhabitants of the maze, each with their own unique backstory. For example, they may appear as traveling performers lost in the maze, guardians who have protected the maze since ancient times, or messengers from another world. The performances will be diverse, including improvisational theater, magic shows, acrobatic movements, singing, and musical performances. Working in conjunction with an AI system, the system will analyze the visitors' dwell time and atmosphere to execute performances at the optimal timing and location. Furthermore, the performance content will be improvised in response to visitor reactions, providing an interactive experience. On special days, surprise appearances by famous artists are also planned, generating buzz on social media. In the surprise performance system, each performer undergoes advanced acting training and is equipped with the ability to respond to improvisational interactions with visitors. Performers receive real-time information from AI via wireless earphones, selecting the most suitable performance based on the visitor's attributes (age, language, group composition) and psychological state (fatigue level, excitement level). For example, they might perform a lighthearted comedy for a children's group, a romantic musical performance for a couple, and nostalgic Showa-era songs for the elderly. Multilingual support is also available, with performances tailored to the language and culture of foreign visitors. Performer placement is optimized by AI analysis of congestion levels and visitor flow within the maze, ensuring that surprising experiences are delivered at appropriate intervals. Furthermore, each performance is recorded on video, and edited commemorative videos are available for a fee to visitors who request them. Regular skill-up training is also conducted for performers, fostering the development of new acts and the refinement of existing ones. Through these comprehensive efforts, an unpredictable, surprising, and moving experience is provided.

[0064] In at least one implementation, an inquiry-based experiential learning program specializing in STEM education will be incorporated into the maze. Numerous experimental puzzles incorporating elements of Science, Technology, Engineering, and Mathematics will be available. For example, participants will assemble solar panel parts to generate electricity and use that power to open a door, or conduct experiments to create specific colors using chemical reactions and have sensors recognize them. Many of the mechanisms utilize the laws of physics, such as calculating the period of a pendulum to press a button at the precise moment, or using the principle of levers to lift a heavy door. In the section on learning about the ecology of living things, participants will solve puzzles by observing actual insects and plants and using their characteristics as clues. Each experiment station will also have explanatory panels on scientific principles, allowing participants to learn the theory after the experience. Special courses aligned with grade-level curricula will also be available for school groups. In the STEM learning program, a specialized science education coordinator will be stationed at each experiment station to provide guidance and support in order to balance the safety of the experiments with the educational effectiveness. The experimental equipment used is educational gear designed with safety as the top priority, and in chemistry experiments, harmless substitutes are used to replicate real chemical reactions. For example, in acid-base reaction experiments, food coloring, baking soda, and citric acid are used to safely observe color changes. Physics experiments include visually engaging challenges such as optical mazes using laser beam reflection and controlling levitation devices using magnetism. Furthermore, integration with digital technology allows students to experience 3D visualizations of molecular structures and simulations of electrical circuits through AR goggles. The success rate of each experiment is recorded as points, and a "Junior Scientist Certificate" is awarded upon reaching a certain point total. In addition, experimental data is saved as individual learning history, and review materials can be accessed online at a later date. Science fairs are also held regularly, providing opportunities to present outstanding experimental results. Through this comprehensive educational program, students can develop scientific thinking skills while having fun.

[0065] In at least one implementation, a comprehensive puzzle-solving system combining multiple academic disciplines will be implemented. Solving one large puzzle will require knowledge and skills from various fields, such as mathematical calculations, historical knowledge, geographical understanding, language deciphering, and scientific experiments. For example, a mission to decipher the code of an ancient civilization will involve multi-stage tasks such as first understanding the historical background, performing calculations using the number system used by that civilization, identifying coordinates on a map, and translating foreign language texts related to that location. The difficulty level of each field can be adjusted from elementary school level to university level, and the most appropriate problems will be presented according to the knowledge level of the participants. In the case of team participation, cooperation by utilizing each member's strengths is encouraged, allowing participants to experience the joy of clearing challenges through the mutual complementarity of knowledge. This interdisciplinary approach will allow participants to learn how to practically apply their knowledge. In the interdisciplinary puzzle-solving system, the challenges will be designed to balance educational value and entertainment, under the supervision of experts in each field. For example, in the theme of "Discovering a Lost Ancient City," a multi-layered puzzle unfolds, starting with archaeological clues, using ancient astronomical knowledge to determine directions from constellations, estimating the age of strata from geological evidence, and deciphering inscriptions using a linguistic approach. Each station also features interactive exhibits that allow participants to learn the basics of that field, enabling even those without prior knowledge to gradually deepen their understanding. Furthermore, AI analyzes the participant's solution process and provides appropriate hints depending on where they are getting stuck. For example, if there is an error in a mathematical calculation, suggestive advice such as "Let's look at the units again" will be displayed. In team competitions, the contribution of each member is visualized, and a system is in place to ensure that everyone can play an active role. In addition, certificates with detailed explanations are issued for excellent answers, enhancing the sense of accomplishment in learning. New puzzle themes are added regularly, providing an environment where repeat participants can continue to enjoy the game.

[0066] In at least one implementation, a recycling craft workshop will be held in conjunction with the maze experience. Participants will create original souvenirs using discarded materials used in the maze's decorations and mechanisms, parts that are no longer needed due to renovations, and recyclable materials brought in by visitors. For example, they may create photo frames using old maze wall panels, light-up keychains incorporating discarded LEDs, and art pieces using used stamps. Craft instructors will be on hand to teach the use of tools such as saws, drills, and glue, while prioritizing safety. Each completed piece will also be tagged with environmental information, such as the origin of the materials used and the amount of CO2 reduced through recycling. A contest will be held regularly, and winning entries will be displayed within the maze. Through this activity, participants will practically learn the concept of "upcycling," which gives new value to waste, and raise awareness of a circular economy. The recycling craft workshop will offer a deeper learning opportunity beyond a simple craft experience, in collaboration with environmental education experts. Participants will first attend a mini-lecture about the manufacturing process and environmental impact of the materials used in the maze. For example, participants gain a deeper understanding of different types and properties of plastics, the recycling rates of metals, and sustainable sourcing methods for wood by handling actual materials. The crafting process emphasizes design thinking that leverages the properties of the materials, tackling creative challenges such as "How can we make use of this bent metal pipe?" or "How can we incorporate LED wiring as part of the design?" Furthermore, scraps generated during the production process are not wasted but sorted and stored for the next participants. Completed works are affixed with an eco-label with a QR code (registered trademark), which, when scanned, displays the work's environmental contribution (CO2 reduction, resource savings) numerically. In addition, creators of outstanding works receive "Eco-Artist Certification" and are offered benefits such as discounts on future maze usage fees. The data collected throughout the year is published as an environmental report and used to visualize the overall environmental contribution of the facility.

[0067] In at least one implementation, a "Green Labyrinth" will be created, featuring abundant green spaces both inside and outside the maze. Living plants will be used as the walls of the maze, allowing visitors to experience the beauty of nature that changes with the seasons. Vertical gardening techniques will be used to cover the entire wall surface with greenery, which is also expected to have an air-purifying effect. The maze will feature themed gardens such as a medicinal herb garden, a vegetable garden, and flowerbeds, each with quizzes and observation tasks related to the plants. For example, visitors may choose their path by relying on the scent of a specific herb or decipher a code using combinations of flower colors. They can also experience simple experiments using seasonal plants (such as observing photosynthesis and comparing seed germination conditions). An automatic watering system and LED supplemental lighting will maintain the healthy growth of the plants throughout the year. Visitors can check the growth records of the plants using a dedicated app and track the growth process of the seeds they planted. This greening will provide a valuable place for nature experiences in an urban area. The design of Green Labyrinth involves horticultural therapists and plant ecologists, who meticulously plan a planting scheme that stimulates the five senses. For the vertical gardens, highly adaptable plants such as ivy, pothos, and philodendron are selected, taking into account their growth rate and ease of maintenance. In the medicinal herb garden area, aromatic plants such as lavender, rosemary, and mint are planted, allowing visitors to touch the leaves and experience their fragrance as they go. In the vegetable garden, visitors can experience harvesting tomatoes, cucumbers, eggplants, and other vegetables depending on the season, and the harvested vegetables are cooked and served at the on-site cafe. A butterfly garden is also installed, with a concentrated planting of nectar-producing plants favored by butterflies, providing a rare opportunity to observe butterflies in an urban area. An automated monitoring system using IoT sensors is implemented for plant management, measuring and adjusting soil moisture, pH, nutrient concentration, etc., in real time. Furthermore, visitor-participation tree-planting events are held regularly, allowing visitors to watch their "My Tree" grow. The program also offers a variety of related activities, such as dyeing experiences using plant-derived natural pigments and pressed flower art workshops, proposing diverse ways to connect with nature.

[0068] In at least one embodiment, a next-generation interactive system combining the latest holographic technology and AI will be introduced. The holograms projected as three-dimensional images into the air are not merely images, but possess a high degree of interactivity that responds to the movements and voices of visitors. For example, it is possible to have a holographic fairy sit on a visitor's palm, or a dragon breathe fire and block a path. These holographic characters are also highly expressive, and their attitudes change depending on their relationship with the visitor. They become cooperative when treated kindly, and sulk when ignored, exhibiting reactions that are almost lifelike. Technically, multiple high-resolution projectors, a special screen, depth sensors, and an AI-based behavior prediction system are integrated. In addition, haptic feedback devices are used to reproduce the feeling of touching the holograms. This technology provides a new dimension of maze experience that blurs the boundaries between reality and virtuality. The implementation of the holographic system combines cutting-edge optical technology and advanced AI control to realize an immersive experience that was previously impossible. Hologram generation employs a phase control method using a laser light source and a spatial light modulator (SLM), projecting 3D images with smooth motion at over 60 frames per second. Visitor position and gaze are tracked in milliseconds by multiple tracking cameras, generating optimal images according to their viewpoint. For example, even if multiple visitors view the same hologram from different angles, accurate 3D images are displayed according to each viewpoint. AI comprehensively analyzes visitors' facial expressions, tone of voice, and gestures to generate responses from the hologram character. For instance, if it detects a child's fear, the hologram dragon softens its intimidating demeanor and changes to a friendly expression. Haptic feedback is achieved through aerial haptic technology using ultrasound, generating a pressure sensation at the point of "touch" the hologram. Furthermore, the hologram character has a learning function, accumulating interaction history with visitors to enable more natural and personalized responses. New hologram characters and interaction patterns are added regularly, constantly providing visitors with fresh surprises.

[0069] In at least one embodiment, an organic design is adopted in which the entire maze system functions as a "living maze." AI controls the entire maze as a single organism, organically responding to visitors' actions. Walls move subtly as if breathing, and passages change shape like peristalsis, giving the feeling of exploring inside the body of a giant organism. Applying the principles of biomimetics, plant growth patterns and animal behavior patterns are incorporated into the changes in the maze. For example, paths that are frequently used by people gain "nutrients" and expand, while unused paths gradually narrow. The "health status" of the entire maze is also monitored, and when visitor satisfaction is high, the maze becomes "energetic" and performs more attractive presentations. This living maze also has its own ecosystem, with virtual organisms moving within the maze and building symbiotic relationships with visitors. This concept makes the maze perceived not merely as a facility, but as an interactive entity. In the "living maze" system, complex biological algorithms and environmental sensor networks are integrated to create a truly organic spatial experience. As the maze's "nervous system," thousands of pressure, temperature, and vibration sensors embedded in the walls and floors sense the presence and actions of visitors in real time. This sensor data is analyzed by a processing system that mimics a neural network and integrated as the overall "sensory" experience of the maze. The movement of the walls is controlled by hydraulic actuators that mimic muscle contractions, and the breathing rhythm changes in sync with the visitor's average heart rate. Furthermore, as a "metabolic system," energy consumption and recovery cycles are set according to the visitor's activity level, with elaborate effects during active times and a shift to energy-saving mode during quieter periods. Virtual creatures are controlled by a swarm intelligence algorithm and "evolve" through interaction with visitors. For example, in areas with many friendly visitors, the creatures learn friendly behavioral patterns, while avoided behaviors are eliminated. In addition, the maze's "memory" system records the behavioral patterns of specific visitors, resulting in more intimate responses upon return visits. These biological characteristics allow visitors to experience the maze not merely as a structure, but as a living entity, fostering a deeper emotional connection.

[0070] In at least one embodiment, an ultrafast path optimization system utilizing quantum computing technology will be implemented. Quantum computers will instantly solve complex optimization problems that would take time to process on conventional computers. Specifically, the system will solve the problem of providing each of the hundreds of visitors simultaneously within a maze while minimizing overall congestion and maximizing individual satisfaction. Quantum annealing and quantum gate models will be used to derive the optimal solution from a vast number of combinations. A "quantum maze" mode, applying the concept of quantum entanglement, will also be available, where the choices of multiple visitors become quantum-intertwined, and the actions of one visitor instantly affect the environment of other visitors located at a distance. Furthermore, a quantum random number generator will produce truly random events, providing unpredictable surprises. This cutting-edge technology will enable an innovative maze experience unlike any other. The implementation of the quantum computing system will employ a hybrid architecture combining cloud-based quantum computing services with edge computing. The quantum annealing machine is specifically designed for combinatorial optimization problems, simultaneously considering multidimensional parameters such as the visitor's current location, destination, personal preferences, fitness level, and group composition to derive the optimal route. For example, it can solve the complex problem of maximizing the satisfaction of 1000 visitors, minimizing waiting times, and optimizing the overall energy efficiency of the facility in seconds by utilizing quantum parallelism. In "quantum maze" mode, multiple rooms in a quantum entangled state are set up, and a visitor's choice in one room (e.g., pressing a red button) instantly affects the environment of another room (the wall color changes to red). This phenomenon allows visitors to experience the wonders of quantum mechanics while simultaneously feeling a mysterious connection with others in distant locations. The quantum random number generator uses radioactive decay and the quantum state of photons to generate truly random numbers, creating events that even AI cannot predict (such as the sudden appearance of a hidden door or the appearance of an unexpected character). Furthermore, quantum machine learning algorithms are used to extract deep-seated characteristics of visitors' behavioral patterns, enabling more accurate personalization.

[0071] In at least one embodiment, the artificial intelligence (AI) system used in the dynamic path-changing maze attraction system of the present invention can be implemented with a variety of AI technologies and is configured to be interchangeable depending on the system requirements and technological advancements. AI technologies that can be employed in this system include, but are not limited to, machine learning, deep learning, reinforcement learning, transfer learning, federated learning, neural networks, convolutional neural networks (CNNs), recurrent neural networks (RNNs), long short-term memory networks (LSTMs), transformers, generative adversarial networks (GANs), variational autoencoders (VAEs), self-organizing maps (SOMs), decision trees, random forests, support vector machines (SVMs), Bayesian networks, genetic algorithms, particle swarm optimization (PSOs), ant colony optimization, fuzzy logic, expert systems, rule-based systems, etc. The flexibility in the AI ​​implementation of this system provides not only technical scalability but also operational adaptability. For example, during initial implementation, it's possible to start with computationally inexpensive decision trees or rule-based systems and gradually transition to more advanced deep learning models as the system matures and the amount of collected data increases. Ensemble learning, which combines multiple AI technologies depending on the nature of the processing, can also be employed. For example, CNNs can be used for visitor face recognition, LSTMs for behavior prediction, reinforcement learning for optimal path calculation, and Transformers for natural language processing; the most suitable technology can be selected for each task. Furthermore, by using edge AI and cloud AI appropriately, distributed processing is possible, where real-time processing (such as visitor fall detection) is performed at the edge, and large-scale training and analysis are performed in the cloud. By adopting federative learning, model improvements can be shared among multiple facilities while protecting privacy.Furthermore, the integration of explainable AI (XAI) technology will enable the visualization of the AI's decision-making process, creating a highly transparent system that operators can understand and verify. A mechanism will also be implemented to compare and evaluate the performance of different AI models through regular A / B testing, ensuring the optimal configuration is always maintained.

[0072] The aforementioned AI technology can be implemented in various forms, including on-premise, cloud, edge computing, fog computing, hybrid, distributed, and centralized. For example, edge AI can be used for visitor motion recognition requiring real-time performance, while cloud AI can be used for large-scale data analysis and learning processes. The optimal implementation can be selected according to the characteristics of the processing. Furthermore, diverse approaches can be adopted for the AI ​​models used, such as pre-trained models, fine-tuning models, zero-shot learning models, fu-shot learning models, multimodal models, and ensemble models. In selecting the implementation form, optimization is performed by comprehensively considering system requirements, costs, scalability, security requirements, etc. In the on-premise type, a high-speed dedicated GPU server is installed within the facility, enabling operation that minimizes latency while preventing sensitive data from being sent externally. On the other hand, in the cloud type, computing resources can be dynamically scaled according to demand, allowing the use of high processing power while keeping initial investment low. In edge computing, small AI processing units are placed in each maze area to achieve immediate response unaffected by network latency. Fog computing involves preprocessing on intermediate servers within the facility, reducing the amount of data transmitted to the cloud, while outsourcing advanced processing to the cloud as needed. A hybrid approach combines these advantages, dynamically selecting the optimal execution environment depending on the processing content. For example, safety-related processing for visitors can be performed at the edge, long-term trend analysis in the cloud, and processing of moderate complexity in the fog. Furthermore, the use of containerization technologies (Docker, Kubernetes) ensures the portability of AI models across different environments.

[0073] The AI ​​system can employ a variety of technologies in natural language processing (NLP), including language models such as BERT, GPT, T5, XLNet, RoBERTa, ALBERT, DistilBERT, Electra, and DeBERTa, or new language models to be developed in the future. For speech recognition, it can employ speech recognition engines such as DeepSpeech, Wav2Vec, Whisper, Kaldi, and Julius, or improved versions of these or newly developed engines. For image recognition, it can use image recognition models such as YOLO, R-CNN, Mask R-CNN, EfficientNet, Vision Transformer (ViT), and CLIP. In the implementation of natural language processing, multilingual support and accuracy of contextual understanding are particularly important. In the interaction interface with visitors, a BERT-based model is fine-tuned to accurately understand maze-specific terminology and instructions. For example, ambiguous requests such as "make it scarier" or "make it enjoyable for children" are appropriately interpreted considering past conversation history and visitor attributes. For multilingual support, the system utilizes multilingual models such as mBERT and XLM-RoBERTa to achieve natural dialogue in over 100 languages. For speech recognition, the Whisper model, combined with noise cancellation technology, is employed to achieve high-precision recognition even in noisy maze environments. Furthermore, region-specific fine-tuning is implemented to accommodate dialects and accents. For image recognition, YOLOv8 enables high-speed object detection to grasp the location and posture of visitors in real time, while Vision Transformer estimates emotional states through detailed facial expression analysis. Additionally, by utilizing CLIP, it becomes possible to integrate image and text understanding, enabling complex situational recognition such as "a child with a happy face." These technologies are used selectively depending on the application; for example, high-speed YOLO is used for safety monitoring, while ViT is used for detailed analysis, selecting the most suitable technology.

[0074] In the hardware implementation of the aforementioned AI system, a variety of processing units, such as CPUs, GPUs, TPUs, NPUs, FPGAs, ASICs, neuromorphic chips, quantum processors, and optical processors, can be used individually or in combination. These processing units can also be dynamically switched according to requirements such as processing load, power consumption, response speed, and cost. Furthermore, existing AI frameworks such as TensorFlow, PyTorch, Keras, Caffe, MXNet, PaddlePaddle, JAX, and ONNX Runtime, or their successor or alternative frameworks, can be adopted. In optimizing hardware implementation, a balance between specialization and generality according to the characteristics of the processing is important. GPUs are widely used for deep learning training and inference, and the latest GPUs, such as NVIDIA's A100 and H100, are particularly suitable for processing large-scale Transformer models. TPUs are specialized for TensorFlow processing on Google Cloud and enable high-speed matrix operations. FPGAs can implement custom circuits optimized for specific algorithms and are used in safety monitoring systems and other applications requiring ultra-low latency. ASICs are used for more specialized processing, for example, as dedicated encryption chips that contribute to protecting personal information. Neuromorphic chips achieve low-power processing by mimicking the neural circuits of the brain and are suitable for always-on sensor systems. Quantum processors demonstrate overwhelming performance in specific combinatorial optimization problems, such as the aforementioned path optimization problems. Optical processors have the potential for ultra-high-speed processing in the future, and experimental introduction at the research and development stage is being considered. These hardware components are dynamically allocated according to the processing content by an integrated management system. For example, flexible operation is possible, such as processing with the CPU and GPU under normal circumstances, additional use of cloud TPUs during peak periods, and activating a quantum processor when a special optimization problem arises.

[0075] The aforementioned AI system employs standardized APIs and data formats to ensure interoperability between different AI technologies. This facilitates migration from one AI technology to another and enables parallel operation of multiple AI technologies. For example, it is possible to replace parts of visitor behavior prediction that previously used machine learning with more accurate deep learning models, or to switch to lighter models depending on computational resource constraints. Furthermore, it is possible to compare the performance of different AI models through A / B testing and select the optimal model. Standard formats such as ONNX (Open Neural Network Exchange) are utilized to achieve interoperability, making it easy to convert models between different frameworks. The API design combines RESTful architecture and GraphQL to provide the optimal interface depending on the application. The data format employs JSON-LD and Protocol Buffers to balance schema extensibility and processing efficiency. MLflow and DVC are used for model version control to ensure the reproducibility of experimental results and the tracking of history. In the implementation of A / B testing, a canary release method is adopted, and the new model is deployed in stages while comparing its performance with the existing model. For example, a new behavioral prediction model can be applied to 5% of visitors, and KPIs such as satisfaction and length of stay can be compared with existing models. Furthermore, techniques such as multi-armed bandits can be used to dynamically evaluate multiple models and automatically converge on the optimal model. In addition, a federated learning framework will be utilized to integrate and learn from data collected from multiple facilities while protecting the privacy of each facility. These technologies will enable the continuous integration of the latest and most optimal AI technologies into the maze system.

[0076] The AI ​​system's training data can also be obtained in a variety of formats and methods. It can handle structured data, unstructured data, semi-structured data, time-series data, spatial data, graph data, multimodal data, etc., and can select from various learning methods such as batch learning, online learning, incremental learning, active learning, semi-supervised learning, self-supervised learning, and unsupervised learning depending on the situation. For data preprocessing, techniques such as normalization, standardization, dimensionality reduction, feature extraction, data augmentation, and denoising can be applied. For advanced data management, a modern data stack combining a data lake and a data warehouse is constructed. Raw data is stored time-series in object storage such as Amazon S3 or Azure Data Lake, and large-scale data transformation is performed by distributed processing using Apache Spark. Structured data includes visitor attribute information, ticket information, movement data, etc., and is managed in a relational database. Unstructured data includes audio, images, videos, text logs, etc., and is managed in a NoSQL database or object storage. Time-series data, including continuous measurements from sensors, is efficiently processed in time-series databases such as InfluxDB and TimescaleDB. Graph data, representing relationships between visitors and path networks within mazes, is managed in graph databases such as Neo4j. For data preprocessing, complex processing pipelines are automated through workflow management using Apache Airflow. Feature engineering combines manual feature design utilizing domain knowledge with automated feature extraction using deep learning. Great Expectations is used to monitor data quality and automatically detect outliers and missing values. To protect privacy, technologies such as differential privacy and homomorphic encryption are applied to ensure data is used in a way that prevents the identification of individuals.

[0077] In terms of security and privacy protection for the aforementioned AI system, a variety of technologies can be employed. Differential privacy, homomorphic encryption, secure multi-party computation, federated learning, blockchain technology, etc., enable AI training and inference while protecting visitor privacy. Furthermore, technologies such as adversarial training, input validation, and model robustness improvement can be implemented as countermeasures against adversarial attacks. For security implementation, a zero-trust architecture is adopted, and a multi-layered defense system is built that verifies all access. Access to the AI ​​model is controlled by authentication and authorization using OAuth 2.0 and JWT tokens, and API calls are protected by rate limiting and IP whitelisting. For differential privacy implementation, Google's differential privacy library is used to add noise to individual contributions, enabling statistical analysis while preventing individual identification. For homomorphic encryption, the Microsoft SEAL library is utilized to enable computation while the data remains encrypted. This allows AI processing to be performed on the cloud without decrypting personal data. As a countermeasure against adversarial attacks, an anomaly detection system for input data is implemented, which automatically detects and isolates inputs with unusual patterns. Furthermore, a system will be introduced to calculate a confidence score for the model's predictions and require human review for predictions with high uncertainty. Blockchain technology will be used to prevent tampering with audit logs, and the history of all AI decisions will be recorded with transparency. Regular penetration testing and security audits will continuously evaluate and improve system vulnerabilities.

[0078] The aforementioned AI system can also incorporate explainable AI (XAI) technology, presenting the rationale behind AI decisions in a human-understandable format through LIME, SHAP, GradCAM, visualization of attention mechanisms, visualization of decision trees, rule extraction, etc. This ensures the transparency and reliability of the system, and facilitates root cause analysis and consideration of improvement measures when problems occur. Furthermore, the ethical aspects of the AI ​​can be designed and operated based on principles such as fairness, accountability, transparency, and privacy protection. The implementation of explainable AI employs a comprehensive approach that combines multiple interpretation methods. LIME provides local explanations for individual predictions, visualizing why a particular route was recommended to a particular visitor. SHAP quantitatively shows the contribution of each feature, clarifying, for example, how much factors such as "age," "group size," and "past behavioral history" influenced the selection of maze difficulty. For deep learning models, visualization of the attention mechanism shows which parts of the input were focused on when making decisions. Furthermore, counterfactual explanations are used to present the boundaries of AI decision-making in an easily understandable way, such as "If X had been the case, a different recommendation would have been made." In the implementation of ethical AI, fairness indicators (demographic parity, equal opportunity, etc.) are continuously monitored to detect and correct biases towards specific attribute groups. For example, if a bias in recommendation content based on gender or age is detected, fairness is ensured by retraining the model or adjusting the weights. In addition, in compliance with international guidelines such as the EU AI Regulation, human supervision (human-in-the-loop) is mandated for high-risk AI uses (such as safety-related decisions). The social impact of the AI ​​system is evaluated through regular ethics committee meetings, and operational policies are reviewed as needed.

[0079] The AI ​​system can also be updated and maintained with flexibility. AI models can be updated without interrupting service through methods such as continuous integration / continuous delivery (CI / CD), model version control, A / B testing, canary releases, rolling updates, and blue-green deployments. Furthermore, optimal performance can be maintained at all times through model drift detection, performance monitoring, and automatic retraining. The entire AI model lifecycle is systematically managed through the implementation of MLOps. Integration with code management using GitLab and GitHub allows for complete tracking of model change history. In the CI / CD pipeline, when a new model is committed, evaluation on a test dataset is automatically performed, and performance metrics (accuracy, latency, memory usage, etc.) are compared with the existing model. In canary releases, the new model is applied to 5% of visitors, and the percentage is gradually increased while confirming that there are no problems. Statistical methods (KS test, PSI, etc.) are used to detect model drift, monitoring changes in the input data distribution, and alerts are issued if a threshold is exceeded. For performance monitoring, a real-time dashboard is built using Prometheus and Grafana, visualizing prediction accuracy, response time, error rate, and more. The automated retraining system automatically initiates a complete retraining process, including hyperparameter optimization, once a certain amount of new data has been accumulated. Furthermore, the Champion-Challenger model ensures that multiple models are evaluated in parallel, and the best-performing model is automatically promoted to the production environment. In the event of a failure, the automatic rollback function allows for immediate reverting to the previous stable version, ensuring service continuity.

[0080] Thus, the dynamic path-changing maze attraction system of the present invention is designed to flexibly adopt, modify, and combine diverse AI technologies without relying on any specific AI technology. This allows for the utilization of the latest and most optimal AI technologies in accordance with technological advancements, ensuring that the system remains obsolete even in long-term operation and continues to provide visitors with the best possible experience. Furthermore, it is possible to select appropriate AI technologies according to different regions, cultures, and regulatory requirements, providing flexibility to support global deployment. The comprehensive flexibility of the AI ​​technologies in this system provides sustainability that can adapt to future technological innovations. Even if new AI technologies that are not currently anticipated emerge, the standardized interface and modular architecture allow for easy integration into the existing system. For example, if brain-computer interface (BCI) technology becomes practical in the future, innovative functions such as directly reading visitors' brainwaves and adjusting the difficulty of the maze can be added. Also, even if the development of quantum machine learning algorithms enables complex pattern recognition that is impossible with current classical computers, it can be introduced without significant changes to the system architecture. In addition, it can flexibly respond to changes in international AI regulations; for example, even if new regulatory requirements such as GDPR or AI laws are added, compliance can be maintained by updating only the relevant modules. Through collaboration with educational and research institutions, a system has been established to rapidly implement the latest research findings, and cutting-edge technologies can always be incorporated through knowledge exchange with academia. This comprehensive flexibility will enable the system to continue functioning as an innovative attraction system that consistently leads the industry, even over long-term spans of 10 or 20 years.

[0081] In at least one embodiment, the dynamic path-changing maze attraction system of the present invention can employ a variety of technologies and implementation methods not only in AI technology but also in all elements constituting the system, and is designed to be flexible and interchangeable according to technological advancements and operational requirements. This versatility makes it possible to operate the system in the optimal configuration at all times without depending on specific technologies or products. This comprehensive flexibility brings significant advantages not only in technical aspects but also in business models and operational forms. For example, small-scale facilities that want to keep initial investment low can start with a basic physical structure and a simple sensor system, and gradually add more advanced technologies as revenue increases. On the other hand, large-scale theme parks can introduce cutting-edge technology from the start to differentiate themselves from competitors. Furthermore, it is possible to select technologies according to regional characteristics; for example, in earthquake-prone areas, a physical structure that prioritizes seismic resistance can be selected, and in hot and humid areas, electronic equipment with excellent waterproof and moisture-proof performance can be selected. In addition, a flexible update strategy according to the technology lifecycle can be planned, and optimization is possible such as updating display technology, which tends to become obsolete quickly, in a short period of time, while using basic structural parts for a long period of time. The design avoids vendor lock-in, mitigating risks such as product discontinuation or price increases from specific manufacturers. Adopting open standards allows for the procurement of optimal components and services from suppliers worldwide, maintaining cost competitiveness. This technical and business flexibility enables sustainable business operations while adapting to diverse market environments and technological changes.

[0082] In the physical structure of the aforementioned maze, a variety of structures and drive methods can be employed, including fixed walls, movable walls, rotating walls, sliding walls, lifting walls, folding walls, telescopic walls, segmented walls, transparent walls, translucent walls, liquid crystal shutter walls, electronic paper walls, hologram walls, air curtains, water curtains, fog screens, laser curtains, magnetic fluid walls, shape memory alloy walls, pneumatically driven walls, hydraulically driven walls, electrically driven walls, and manually driven walls. These can be used individually or in combination and can be selected and changed according to requirements such as budget, safety, visual effect, and maintainability. When selecting the physical structure, it is important to choose the optimal combination that takes advantage of the characteristics of each technology. Fixed walls form the basic maze structure and are used in the main structural parts due to their excellent durability and cost efficiency. Movable walls are controlled by hydraulic or electric actuators and can rotate 90 degrees or slide 2 meters in less than 1 second, playing a central role in dynamic path changes. Liquid crystal shutter walls instantly change transparency from 0% to 100% through voltage control, creating visual surprises. Air curtains create an invisible wall using high-speed airflow, functioning as a mysterious barrier that can only be passed through under specific conditions. Mist screens project images onto tiny water droplets, creating a passable visual wall and, combined with holographic effects, generating a fantastical space. Magnetic fluid walls change shape freely through magnetic field control, enabling organic and lifelike wall surfaces. Shape memory alloy walls deform into pre-programmed shapes in response to temperature changes, creating interactive walls that react to visitors' body temperature and ambient temperature. These technologies are linked to safety sensors, incorporating a safety mechanism that automatically stops when a person approaches a moving part. Regular maintenance schedules manage the lifespan and replacement timing of each structure, ensuring that it is always maintained in optimal condition.

[0083] The aforementioned sensor means can be selected and combined from a wide variety of sensors depending on the situation, including optical sensors (visible light cameras, infrared cameras, ultraviolet cameras, hyperspectral cameras, ToF cameras, stereo cameras, 360-degree cameras), acoustic sensors (microphones, ultrasonic sensors, vibration sensors), position detection sensors (GPS, Bluetooth, Wi-Fi, UWB, RFID, NFC, geomagnetic sensors, acceleration sensors, gyroscopes), environmental sensors (temperature sensors, humidity sensors, barometric pressure sensors, illuminance sensors, UV sensors, gas sensors, dust sensors), biosensors (heart rate sensors, body temperature sensors, blood pressure sensors, respiration sensors, electroencephalogram sensors, electromyography sensors, skin electrical activity sensors), pressure sensors, weight sensors, capacitance sensors, proximity sensors, LiDAR, radar, sonar, etc. Multimodal sensing and sensor fusion technologies play an important role in the integration of the sensor system. The optical sensor group enables high-precision tracking of visitor positions, facial expression recognition, and gesture detection, and for example, an 8K resolution camera enables motion detection down to the millimeter. The combination of ToF cameras and stereo cameras enables accurate 3D positioning even in low light conditions, allowing for real-time assessment of distances between visitors and the risk of contact with walls. Acoustic sensor arrays selectively collect sound from specific directions using beamforming technology, accurately recognizing individual visitor speech even in noisy environments. UWB sensors achieve indoor positioning with an accuracy of less than 10 centimeters, enabling precise location tracking even in environments where GPS is unavailable. Environmental sensors monitor the maze environment from both comfort and safety perspectives; for example, the ventilation system automatically activates if the CO2 concentration exceeds 1000 ppm. Biosensors, using wearable devices and non-contact sensing technology, continuously monitor visitors' physiological states, dynamically adjusting the maze difficulty according to stress levels and fatigue. All of this sensor data is preprocessed at edge computing nodes, and only necessary information is sent to the cloud, optimizing both bandwidth and privacy.

[0084] The aforementioned display devices can employ a variety of display technologies, including liquid crystal displays (LCDs), organic light-emitting diodes (OLEDs), inorganic light-emitting diodes (ELs), plasma displays, electronic paper (E-ink), LED displays, micro-LED displays, mini-LED displays, quantum dot displays (QLEDs), projectors (DLP, LCD, LCoS, laser), hologram displays, volumetric displays, transparent displays, flexible displays, curved displays, spherical displays, multi-faceted displays, head-mounted displays, retinal projection displays, aerial displays, water vapor displays, and physical displays using sand or particles. In selecting and arranging display technologies, it is important to design an immersive visual experience that makes the most of the characteristics of each technology. Organic light-emitting diodes are ideal for creating horror effects in dark maze environments due to their perfect black reproduction and wide viewing angle characteristics, and multiple OLED panels embedded in a wall can work together to create an effect like the eyes of a giant creature. Micro-LED displays take advantage of their ultra-high brightness (over 10,000 nits) and long lifespan to ensure visibility in outdoor areas and bright environments. Electronic paper, leveraging its ultra-low power consumption and high visibility in sunlight, is used for directional signs and variable warnings within the maze. Laser projectors, capable of long-distance projection of over 100 meters, project dynamic visual effects onto the maze's ceiling and floor. Holographic displays, utilizing Pepper's Ghost technology and the latest light field displays, create three-dimensional images floating in mid-air, displaying ethereal, intangible guide characters. Transparent displays function as transparent walls under normal circumstances, displaying information and images when needed, maintaining a sense of openness while providing information. Curved and spherical displays enable 360-degree viewing, with a centrally located spherical display showing a map of the entire maze and the visitor's location in real time. These display devices are synchronized and controlled by an integrated control system, allowing multiple displays to work together to form a single, massive visual space.

[0085] The aforementioned sound system allows for the selection of a variety of acoustic technologies, including dynamic speakers, condenser speakers, ribbon speakers, electrostatic speakers, piezoelectric speakers, bone conduction speakers, directional speakers, parametric speakers, planar speakers, vibration speakers, ultrasonic speakers, subwoofers, tweeters, midrange speakers, full-range speakers, line arrays, surround sound systems (5.1ch, 7.1ch, 9.1ch, 11.1ch, 22.2ch, etc.), object-based audio (Dolby Atmos, DTS:X, etc.), binaural recording and playback systems, wavefield synthesis, and ambisonics. The implementation of the sound system aims to create a sophisticated auditory experience by combining the principles of spatial acoustic design and psychoacoustics. Directional speaker arrays utilize ultrasonic sound beam technology to deliver sound only to visitors at specific locations, providing different acoustic experiences to multiple groups even when they are in close proximity within a maze, for example. Parametric speakers utilize the nonlinearity of air to "place" sound at specific points up to 50 meters away, creating the illusion of an invisible presence whispering. Bone conduction speakers provide personalized audio guidance through dedicated headsets or neckbands without blocking out ambient sounds. Subwoofer arrays generate ultra-low frequencies below 20Hz, physically creating feelings of fear and tension through vibrations felt throughout the body. 22.2ch surround sound systems reproduce a three-dimensional sound field including height, and can also represent vertical acoustic movement, such as objects flying overhead or sounds rising from below. Object-based audio allows sound sources to be placed and moved to any position in space, creating unrealistic acoustic experiences such as sounds that follow the visitor's movements or sounds that pass through walls. Furthermore, frequency response adjustments based on psychoacoustics enable acoustic design that directly appeals to emotions, such as dissonances that amplify feelings of anxiety or harmonic structures that provide a sense of security.

[0086] Regarding the aforementioned communication methods, a variety of communication methods can be selected and used in combination depending on the application, including wired communication (Ethernet, optical fiber, coaxial cable, USB, HDMI®, DisplayPort, Thunderbolt, RS-232C, RS-485, CAN, I2C, SPI), wireless communication (various Wi-Fi standards, various Bluetooth versions, Zigbee, Z-Wave, LoRa, Sigfox, NB-IoT, LTE-M, 5G, 6G, satellite communication, infrared communication, visible light communication, sound wave communication, magnetic field communication), and short-range wireless communication (NFC, FeliCa®, various RFID frequency bands). In designing the communication system, the optimal technology selection is made considering the balance between real-time performance, reliability, security, and scalability. A fiber optic backbone of 10Gbps or more is constructed for the core network, transmitting large amounts of data to the edge nodes in each area with low latency. 5G / 6G communication utilizes the millimeter wave band to achieve ultra-low latency communication of less than 1ms, enabling high-definition video streaming for VR / AR devices and real-time distribution of AI processing results. Wi-Fi 6E / 7 utilizes the 6GHz band to provide stable, high-speed communication even in densely populated environments, maintaining communication quality even when hundreds of visitor devices are connected simultaneously. LPWAN technologies such as LoRa and Sigfox are used in various battery-powered sensors, enabling continuous operation for more than 5 years with just two AA batteries. Visible light communication (Li-Fi) uses LED lighting for data communication, achieving communication speeds of over 100Mbps even in environments where radio waves cannot be used. Experimental introduction of quantum cryptography technology establishes a theoretically unbreakable communication path, which is used for transmitting personal information requiring the highest level of security. Furthermore, mesh network technology automatically forms a bypass route even if some communication equipment fails, ensuring fault tolerance for the entire system. By linking with edge computing, critical data is processed on-site, minimizing the amount and latency of data transmitted to the cloud.

[0087] The aforementioned lighting system allows for the selection of a variety of lighting technologies according to the performance requirements, including incandescent bulbs, fluorescent lamps, LEDs, organic EL lighting, inorganic EL lighting, laser lighting, fiber optic lighting, neon tubes, plasma lighting, HID lamps, halogen lamps, xenon lamps, blacklights, strobe lights, moving lights, spotlights, wash lights, beam lights, laser projectors, gobo projectors, pinspots, follow spots, uplights, downlights, indirect lighting, RGB LEDs, RGBW LEDs, color-tunable LEDs, addressable LEDs, etc. The implementation of the lighting system involves multi-layered lighting environment design, ranging from biocompatible lighting that considers circadian rhythms to dramatic performance effects. The color-tunable LED system continuously changes color temperature from 2700K to 6500K, optimizing visitor alertness according to the time of day. For example, in the morning, a bluish-white light of 6500K is used to enhance activity, while in the evening, a warm light of 2700K is used to create a relaxing effect. Addressable LED strips, by independently controlling individual LED elements, generate light waves and flowing animation effects, creating light trails that follow the movement of visitors. Laser lighting systems, combined with smoke and mist, create three-dimensional light structures in the air, forming an intangible maze of light. Moving lights, precisely controlled via the DMX512 protocol, automatically perform spotlight-like effects while tracking visitors' positions in real time. Organic EL lighting utilizes its surface-emitting properties to provide soft, shadowless light, creating an eye-friendly lighting environment in rest areas. Blacklight effects, combined with UV-reactive special paint, reveal normally invisible images and letters, providing important clues for solving puzzles. Furthermore, the lighting control system works in conjunction with AI to dynamically adjust the brightness, color, and movement of the lighting according to the emotional state of visitors and the congestion level of the maze, automatically generating the optimal atmosphere.

[0088] The aforementioned power supply system can employ a variety of power supply methods, including commercial power, solar power, wind power, hydroelectric power, geothermal power, biomass power, fuel cells, storage batteries (lithium-ion batteries, sodium-ion batteries, all-solid-state batteries, flow batteries, lead-acid batteries, nickel-metal hydride batteries), supercapacitors, flywheels, compressed air energy storage, pumped-storage hydropower, uninterruptible power supplies (UPS), generators, and energy harvesting (vibration power generation, thermoelectric power generation, piezoelectric power generation). The power supply system design implements multi-layered energy management considering reliability, sustainability, and economic efficiency. While using commercial power as the primary power source, solar panels installed on the facility's rooftop (total output 500kW) cover 30% of the daytime peak power demand. A lithium-ion battery system (capacity 2MWh) reduces power costs by storing inexpensive electricity at night and discharging it during daytime peaks. Experimental introduction of all-solid-state batteries achieves five times the charge-discharge cycle life of conventional batteries and a significant reduction in fire risk. Wind power generation utilizes vertical-axis wind turbines depending on the wind conditions around the facility, enabling efficient power generation even at low wind speeds. The fuel cell system uses hydrogen as fuel and guarantees continuous operation for more than 72 hours even during power outages. Supercapacitors absorb instantaneous fluctuations in power demand, such as covering inrush currents during the simultaneous operation of large movable walls. Energy harvesting technology converts vibrations from visitors walking and waste heat from the air conditioning system into electricity, which is used as an auxiliary power source for the sensor network. In addition, an AI-based energy management system comprehensively analyzes weather forecasts, visitor count forecasts, and electricity market prices to automatically select the most economical and environmentally friendly power mix. In the event of a power outage, the UPS instantly activates, maintaining power supply to critical systems while seamlessly switching to emergency generators.

[0089] The aforementioned materials include metals (iron, aluminum, titanium, magnesium, various alloys), plastics (ABS, polycarbonate, acrylic, nylon, PEEK), composite materials (CFRP, GFRP, Kevlar®), wood (solid wood, laminated wood, plywood, MDF), glass (tempered glass, bulletproof glass, dimmable glass, conductive glass), ceramics, concrete, stone, fabric, paper, biomaterials, recycled materials, 3D printed materials, shape memory materials, self-healing materials, phase change materials, metamaterials, etc., which can be selected according to the application and required performance. In material selection, an integrated material design is carried out considering the balance of functionality, sustainability, aesthetics, and cost. By using carbon fiber reinforced plastic (CFRP) for structural members, it is possible to achieve equivalent or greater strength with 1 / 5 the weight of steel, achieving weight reduction and energy saving for large-scale movable structures. Self-healing materials realize maintenance-free walls by automatically releasing and hardening a repair agent encapsulated in microcapsules when cracks occur. Shape memory alloys, using materials such as nitinol, are utilized as movable parts that deform into pre-programmed shapes in response to temperature changes. Metamaterials possess special structures that control the propagation of light and sound; for example, acoustic metamaterials can form "sound walls" that block only sounds of specific frequencies. Biomaterials utilize thermal insulation and sound-absorbing materials made from cultured mycelium, which are environmentally friendly interior materials that are completely biodegradable after use. 3D printing technology allows for the on-demand production of complex decorative parts using recycled plastics, reducing inventory costs and increasing design flexibility. Phase change materials (PCMs) utilize latent heat associated with temperature changes to function as a passive air conditioning support system that maintains a constant temperature within a maze. Furthermore, each material is embedded with an RFID tag, recording information such as the manufacturing date, start date of use, expected lifespan, and recycling method, enabling optimal management throughout the entire lifecycle.

[0090] The aforementioned environmental control system can be used in combination with air conditioners (central air conditioning, individual air conditioning, VRF, district heating and cooling), ventilation systems (natural ventilation, mechanical ventilation, hybrid ventilation, heat exchange ventilation), humidifiers (ultrasonic, heated, evaporative, hybrid), dehumidifiers (compressor, desiccant, Peltier), air purifiers (HEPA, activated carbon, photocatalyst, plasma, ozone), sterilization and disinfection systems (UV-C, ozone, hypochlorous acid, photocatalyst), fragrance generators (aroma diffusers, aerosols, microcapsules), ion generators, etc. The implementation of the environmental control system involves advanced air conditioning control that comprehensively optimizes comfort, health, and energy efficiency. The VRF (Variable Refrigerant Flow) system individually controls the refrigerant flow rate according to the heat load of each area, achieving high-efficiency operation with a COP (Coefficient of Performance) of 6.0 or higher even at partial load. Demand-controlled ventilation (DCV) optimizes the amount of outside air intake in conjunction with a CO2 sensor, reducing the air conditioning load by 30% while maintaining indoor air quality with minimal ventilation. The air purification system, combining a HEPA filter and a UV-C germicidal lamp, removes 99.97% of 0.3μm particles and simultaneously inactivates bacteria and viruses in the air. The photocatalytically coated walls decompose organic matter even under visible light, providing sustained deodorizing and antibacterial effects. The aroma diffuser system, linked to visitor location information, provides different scents in each area, creating a memorable olfactory experience. For example, the forest area is filled with the scent of pine and cypress, while the sea area is filled with the scent of the ocean. Furthermore, AI-based predictive control forecasts the air conditioning load 30 minutes in advance based on the number of visitors, outside temperature, and solar radiation, automatically generating an optimal operating plan. To accommodate individual differences in thermal sensitivity, localized air conditioning control is also possible based on biometric information from wearable devices. The energy recovery system recovers thermal energy from exhaust and uses it for preheating and precooling the intake air, thereby reducing annual energy consumption by 40%.

[0091] The aforementioned safety system can appropriately incorporate surveillance cameras (fixed, PTZ, omnidirectional, thermal, license plate recognition), access control (IC card, biometric authentication, facial recognition, iris recognition, vein recognition, voice recognition), intrusion detection (infrared sensors, microwave sensors, vibration sensors, acoustic sensors), fire detection (smoke detectors, heat detectors, flame detectors, gas detectors), fire extinguishing equipment (sprinklers, foam extinguishing, gas extinguishing, powder extinguishing), evacuation guidance (guide lights, voice guidance, flashing lights, evacuation route displays), emergency notification (emergency buttons, intercoms, automatic notification), AEDs, first-aid kits, wheelchairs, stretchers, etc. The safety system design establishes a comprehensive safety management system based on a four-stage approach: prevention, detection, response, and recovery. AI-powered behavioral analysis cameras automatically detect falls, sudden illnesses, lost children, suspicious behavior, etc., and notify the security center within one second. Thermal cameras not only screen for people with fevers but also identify visitors at high risk of heatstroke in advance and provide guidance on preventative hydration. The biometric authentication system uses multi-factor authentication combining face, fingerprint, and vein patterns to reliably prevent impersonation. The fire detection system integrates flame detection using image recognition, smoke detection using gas sensors, and heat detection using temperature sensors, achieving high-precision detection with a false alarm rate of less than 0.01%. Fire extinguishing equipment is optimized according to the characteristics of each area, with gas extinguishing systems in electrical equipment areas and sprinklers in general areas, ensuring appropriate placement. The evacuation guidance system dynamically generates the optimal evacuation route considering real-time congestion levels, and embedded LED floor guide lights indicate evacuation routes that are visible even in smoke. One AED is always placed within 50 meters and automatically notifies the nearest medical staff when used. In addition, all staff receive regular life-saving training, and a system is in place to ensure that trained staff equivalent to 3% of visitors can arrive at the scene within 5 minutes in the event of an emergency.

[0092] For the aforementioned data processing and storage system, servers (physical servers, virtual servers, cloud servers, edge servers), storage (HDD, SSD, NVMe, SAN, NAS, object storage, tape storage), databases (relational, NoSQL, graph, time series, in-memory), data processing infrastructure (Hadoop, Spark, Flink, Storm), container technologies (Docker, Kubernetes, OpenShift), serverless technologies (AWS Lambda, Azure Functions, Google Cloud Functions), etc., can be selected according to requirements. In the implementation of the data processing and storage system, the optimal architecture is built to meet the requirements of real-time processing, batch processing, and long-term storage. Edge servers are distributed throughout each maze area, and high-performance edge AI computers such as NVIDIA Jetson AGX Orin perform processing such as video analysis and speech recognition with a latency of less than 1 millisecond. The time series database (InfluxDB) ingests sensor data of more than 1 million data points per second, enabling real-time anomaly detection and trend analysis. The graph database (Neo4j) efficiently manages relationships between visitors and interactions within the maze, and is used for analyzing social dynamics. Apache Spark is used as the distributed processing platform, parallel processing of several terabytes of log data accumulated daily to improve operations the following day. Container orchestration (Kubernetes) automatically scales containers according to processing load, ensuring stable service even during peak periods. Amazon Glacier is used for cold storage, achieving the legally mandated 7-year data retention at low cost. Blockchain technology is also partially implemented to record important transaction records and access logs to personal information in an tamper-proof manner. Data lifecycle management automatically selects the optimal storage medium based on access frequency: NVMe SSDs for hot data, HDDs for warm data, and tape storage for cold data.

[0093] The aforementioned energy efficiency technologies can utilize inverter control, power factor correction, demand control, peak shaving, thermal and thermal storage, cogeneration, heat pumps, geothermal energy utilization, solar thermal energy utilization, waste heat recovery, energy management systems (EMS, BEMS, FEMS), smart grid integration, virtual power plant (VPP) participation, carbon offsetting, and green power certificates. In implementing energy efficiency, AI-powered predictive control and optimization will achieve energy savings of over 50% compared to conventional systems. Inverter-controlled air conditioning and lighting systems continuously adjust rotation speed and illuminance according to the load, maximizing efficiency at partial load. Power factor correction devices maintain a power factor of 0.95 or higher, minimizing losses due to reactive power. The demand forecasting system predicts electricity demand in 30-minute intervals with an accuracy of ±5% based on past usage patterns, weather forecasts, event schedules, etc., preventing exceeding contracted power. The thermal storage tank (1000-ton capacity) reduces peak power consumption by 40% by using nighttime electricity to make ice, which is then used for daytime cooling. The geothermal heat pump utilizes the stable underground temperature of around 15°C throughout the year, achieving high-efficiency operation with a COP of 5.0 or higher. The cogeneration system generates electricity with a gas engine while using waste heat for hot water supply and heating, achieving an overall efficiency of 85%. The BEMS visualizes all energy usage within the facility in real time, and when abnormal consumption is detected, the AI ​​automatically identifies the cause and proposes improvements. By participating in the VPP, the battery storage and private power generation equipment are utilized in the electricity market, generating several million yen in additional revenue annually. Furthermore, by utilizing the J-Credit scheme, the amount of CO2 reduction achieved through energy conservation activities is certified and sold, achieving both environmental contribution and economic benefits.

[0094] Thus, the dynamic path-changing maze attraction system of the present invention offers diverse options for all components, including not only AI, but also physical structure, sensors, display devices, acoustics, lighting, communication, power supply, materials, environmental control, safety systems, and data processing, allowing for free combination and replacement of these components. This design philosophy enables flexible adaptation to various changes in conditions, such as technological advancements, local regulations, budget constraints, operational requirements, and visitor needs, ensuring that the attraction is always operated in an optimal configuration. Furthermore, partial updates and modifications are easy, allowing for the upgrade of only the necessary parts to the latest technology without replacing the entire system. This flexibility and scalability ensures that the attraction remains attractive and sustainable even in long-term operation without becoming obsolete. This comprehensive freedom of technology selection provides operators with a strategic competitive advantage. For example, if competitors are building systems that rely on specific technologies, this system can differentiate itself with a completely different technological approach. It also allows for a phased implementation strategy that considers the technology maturity curve, enabling risk management by verifying new technologies in small pilot areas and then fully deploying them after their performance is confirmed. Furthermore, localization tailored to regional characteristics is easy. For example, in earthquake-prone Japan, seismic resistance can be prioritized; in hot and humid Southeast Asia, cooling and dehumidification functions can be enhanced; and in Europe, where privacy regulations are strict, data protection functions can be particularly strengthened. Collaboration with technology partners is also flexible, allowing for partnerships with best-of-breed companies in each field without relying on specific vendors. Moreover, the open innovation framework allows for the active incorporation of innovative technologies from startup companies. This combination of technological flexibility and business agility makes it possible to consistently deliver cutting-edge experiences in the rapidly changing entertainment industry.

[0095] In at least one embodiment, a "personalized exclusion system" will be implemented that excludes specific attractions based on visitors' physical characteristics and personal preferences. When visitors enter or make reservations in advance, they will input information such as whether they are prone to motion sickness, have acrophobia, nyctophobia, dislike loud noises, dislike intense movements, have a heart condition, are pregnant, have back pain, neck or back problems, are prone to dizziness, are claustrophobic, dislike water, dislike animals, or are allergic to certain smells. AI will analyze this information and automatically identify attraction elements deemed inappropriate for the visitor, suggesting routes that exclude those elements when selecting a route within the maze. For example, areas containing spinning elements or intense vertical movements will be avoided for visitors prone to motion sickness, and routes containing high-altitude performances will be excluded for visitors with acrophobia. As the personalized exclusion system becomes more sophisticated, it will offer not only simple exclusions but also gradual adaptation programs. For example, visitors with mild nyctophobia (fear of darkness) can start in a dimly lit area and gradually increase the level of darkness in a "gradual desensitization program." Biological responses (heart rate, skin electrical activity, etc.) are monitored at each stage, and the brightness is automatically adjusted if the stress level exceeds a threshold. Exclusion settings can also be dynamically updated, allowing for immediate changes via voice commands or gestures if a visitor experiences a change in their physical condition during the experience. Consideration is also given to group visits; if exclusion settings differ among members, the AI ​​suggests an optimal common route that everyone can enjoy. Furthermore, alternative experiences are provided based on the reason for exclusion; for example, visitors who have excluded strenuous activity are offered a static yet intellectually stimulating puzzle-solving challenge. Integration with medical data (with the visitor's consent) ensures a safer experience by considering factors such as prescription drug side effects and recent surgical history. Long-term data analysis identifies common exclusion patterns among visitor groups with specific attributes, which are then used to improve facility design.

[0096] The personalized exclusion system employs a detailed classification system based on medical evidence. Each attraction element is quantified using indicators such as the degree of vestibular stimulation, the intensity of visual stimulation, the level of auditory stimulation, the degree of physical exertion, the expected increase in heart rate, and the degree of stress induction. Visitors can set their exclusion preferences in three stages: mild, moderate, and severe. For mild settings, a gradual acclimatization program to similar experiences is also proposed. Medical information such as doctor's diagnoses and pharmacist's warnings is also considered to ensure a safety-oriented assessment. For pregnant visitors, detailed guidelines are applied according to the gestational week, and attractions containing stimuli or movements unsuitable for each stage are automatically excluded. The implementation of the medical classification system is supervised by multiple medical experts, and the latest medical knowledge is continuously reflected. The degree of vestibular stimulation is quantified using physical parameters such as angular acceleration, linear acceleration, and vibration frequency, and is compared with a motion sickness sensitivity score. Visual stimuli are evaluated based on contrast ratio, flashing frequency, and field of view angle change rate, and the risk of photosensitive seizures is scientifically assessed. Auditory stimuli are classified based on sound pressure level, frequency characteristics, and rapid volume changes, and adjustments are made according to the degree of hyperacusis or hearing loss. Guidelines for each stage of pregnancy avoid strong vibrations and rapid changes in air pressure in the first trimester (up to 12 weeks), limit prolonged standing and extreme temperature environments in the second trimester (13 to 27 weeks), and completely eliminate elements that increase the risk of falls in the third trimester (from 28 weeks). By linking with a drug interaction database, individual precautions for users of anti-vertigo drugs, antihypertensive drugs, psychotropic drugs, etc. are automatically generated. Furthermore, by utilizing knowledge from rehabilitation medicine, load limits for visitors with orthopedic conditions (herniated discs, osteoarthritis, etc.) are precisely calculated. These medical considerations achieve an optimal balance between entertainment and medical safety.

[0097] The system includes exclusion and alternative suggestion functions that take into account the relationship with companions. For example, if one family member excludes a particular attraction, the AI ​​automatically generates an alternative route that the whole family can enjoy. Furthermore, if exclusion settings differ within a group, a split route system is provided that temporarily separates the group, allowing them to experience different routes before reuniting them at a designated meeting point. For excluded visitors, special programs offering equivalent enjoyment (static puzzle-solving, gentle presentations, educational content, relaxation experiences, etc.) are provided, ensuring they can enjoy the maze experience without feeling left out. The relationship-based exclusion system implements advanced algorithms to analyze group dynamics. In the case of families, a "family safety score" is calculated to balance the protective instincts of parents with the adventurous spirit of children, automatically setting an experience level that everyone can enjoy safely. For couples, if a mismatch is detected, such as one being easily frightened and the other a thrill-seeker, a "couple harmony plan" is created, allowing each person to alternately experience areas suited to their preferences, ultimately leading to a romantic finale where they cooperate. In friend groups, a "support system" is activated, providing a mechanism (parallel routes, voice calls, encouraging messages, etc.) that allows other members to support members who are feeling scared. Addressing generational gaps is also well-established; for example, if grandparents and grandchildren visit together, a "three-generation satisfaction program" is available that considers the grandparents' physical capabilities while satisfying the grandchildren's curiosity. When using split routes, the progress of each group is shared in real time, with live updates such as "The dads' team is currently tackling the puzzles!" broadcast to other teams. At the meeting point, special arrangements are made to share each group's experience (simultaneous playback of experience videos, exchange of acquired items, etc.), ensuring that being separate actually becomes a special memory.

[0098] The exclusion system also incorporates a gradual overcoming program called the "Phobia Graduation System." If requested by the visitor, a program is offered to help them gradually become accustomed to the excluded stimuli. For example, a visitor with mild acrophobia would start with a low observation area about 50 cm from the ground and gradually increase in height over multiple visits. The visitor's physiological responses (heart rate, sweating, facial expressions, etc.) are monitored at each stage to ensure the program progresses at a comfortable pace. The goal is to build confidence through a series of successful experiences, ultimately enabling the visitor to enjoy the attractions that were initially excluded. This program also includes supervision by professional psychological counselors and occupational therapists. The implementation of the Phobia Graduation System employs a scientific approach based on the principles of cognitive behavioral therapy (CBT). In the initial assessment, a standardized phobia assessment scale (e.g., Acrophobia Questionnaire) is used to quantify the degree of fear on a score of 0-100. Through VR-based pre-experiences, participants gradually expose themselves in a virtual environment before entering the actual maze, enhancing their readiness. Each session incorporates relaxation techniques (deep breathing, progressive muscle relaxation) to control anxiety while progressing through the exposure process. Successful experiences are recorded as "courage points," and "fear-overcoming badges" are awarded upon reaching a certain point threshold, strengthening motivation through gamification elements. A dedicated community for program participants is also provided, allowing for information exchange and mutual encouragement among those with similar phobias. A support guide for families is also offered, including specific advice on "how to encourage" and "what to avoid" to enable companions to provide appropriate support. Long-term follow-up studies scientifically verify the program's effectiveness, enabling continuous improvement. Collaborative research with academic institutions will contribute to the advancement of phobia treatment, realizing the creation of new value through the fusion of entertainment and medicine.

[0099] The system, in conjunction with real-time health monitoring, can respond to changes in a visitor's physical condition on the day of their visit. Even if there are no problems upon entry, if a visitor experiences discomfort or increased anxiety during their maze experience, exclusion settings can be updated in real time based on sensor data from wearable devices and visitor reports. For example, if a visitor experiences mild dizziness in the maze, they will be immediately guided to the nearest rest area, and subsequent areas containing rotational elements will be automatically excluded. It is also possible to temporarily exclude visitors during specific time periods (menstrual period, after medication, after meals, etc.). Changes in physical condition due to weather and season (barometric pressure sensitivity, hay fever, fatigue from temperature changes, etc.) are also taken into consideration, and an automatic adjustment function linked to weather data is provided. The real-time health monitoring system implements an advanced algorithm that comprehensively analyzes data from multiple biosensors. Heart rate variability (HRV) analysis evaluates the balance of the autonomic nervous system and quantifies the stress level in five stages. Continuous measurement of skin electrical activity (EDA) detects emotional sweating and allows for real-time assessment of the degree of anxiety and excitement. The gait analysis using acceleration sensors detects unsteadiness and decreased walking speed, enabling early detection of fatigue and poor health. This data is processed instantly on-site by edge AI, and a health assessment and countermeasures are determined within one second. The weather-linked function matches environmental data such as atmospheric pressure change rate, temperature change, humidity, and pollen count with an individual's medical history (migraine, asthma, allergies, etc.) to predict the risk of worsening health. For example, visitors with a history of migraines will be guided to less stimulating routes when a low pressure system is approaching. The medication management function records the type and time of medication administration, and automatically sets appropriate time-based restrictions on experiences based on the side effect profile (drowsiness, dizziness, photosensitivity, etc.). For female visitors, the system is linked with a menstrual cycle tracking function to adjust the experience to accommodate sensory sensitivities during PMS. This comprehensive health management ensures that all visitors can enjoy the experience with peace of mind.

[0100] The exclusion system also incorporates cultural and religious considerations. Elements that visitors with specific religious backgrounds may want to avoid (certain animals, music, colors, symbols, physical contact, etc.) are pre-configured, and areas containing such performances or exhibits are automatically excluded. Furthermore, performance adjustments are made to accommodate cultural taboos, food allergies, and lifestyles such as veganism and vegetarianism. By respecting diversity and providing an environment where all visitors can enjoy themselves comfortably, an inclusive entertainment space is realized. These settings are highly encrypted, and privacy is strictly protected. The implementation of the cultural and religious considerations system involves the development of comprehensive guidelines by international cultural experts and religious scholars. For Muslims, the exclusion of pig-related performances, consideration for prayer times (Salat), and halal food options are automatically configured. For Hindus, cow-like characters are hidden, and vegetarian experiences are prioritized. For Jewish visitors, a manually operable alternative route is provided to accommodate the use of electronic devices during the Sabbath (Shabbat). For Buddhists, the option to exclude performances that evoke killing is offered. Cultural considerations include avoiding handing objects with the left hand for visitors from the Middle East and avoiding head contact for visitors from Asia. For the LGBTQ+ community, gender-neutral performance options and romantic performances for same-sex couples are provided. Regarding food, not only allergy information but also dietary restrictions due to religious and ethical reasons (halal, kosher, vegan, etc.) are considered, and alternatives are automatically provided for experiences involving food and drink. Furthermore, the event is linked to a cultural holiday calendar, automatically excluding daytime performances involving food and drink during Ramadan, for example. These comprehensive considerations ensure a truly global entertainment experience where visitors from all cultural backgrounds around the world can enjoy themselves while having their identity respected.

[0101] Improvement system based on statistical analysis The aforementioned system will also be used to improve attraction design through statistical analysis of excluded data. By identifying elements that many visitors exclude and problematic performance patterns in specific combinations, it will be useful in developing attractions that are accepted by a wider range of visitors. Furthermore, for elements with high exclusion rates, improvement measures such as developing milder alternative performances or adding intensity adjustment functions will be considered. Long-term data accumulation will also allow for analysis of regional and cultural characteristics and age-specific trends, providing important guidelines for the international expansion and new development of facilities. This will enable the design of universal attractions that can be enjoyed by everyone without excluding any particular group. Detailed Implementation: Machine learning algorithms are used to perform correlation analysis of exclusion patterns, yielding insights such as "the overlap rate between acrophobia and nyctophobia is 67%." Regional analysis reveals that visitors from Asia are 1.3 times more sensitive to auditory stimuli than those from Europe and the US. Age-based analysis identifies that Generation Z reacts less to traditional horror effects and prefers AR / VR elements (resulting in a 15% increase in satisfaction). Based on these findings, an alternative effect library is constructed, developing, for example, a simulated rotation experience using visual illusions instead of intense rotation elements. Gradual intensity adjustment allows for 10 levels of stimulation to accommodate a wide range of tolerance levels within the same attraction. For international expansion, a database of cultural characteristics in each country is utilized to implement an automatic compliance function with local laws and regulations (e.g., EU accessibility directives). As a quantitative evaluation of the improvement effect, correlation analysis of monthly changes in exclusion rates, acceptance rates of alternative effects, and customer satisfaction scores is continuously conducted.

[0102] Time Management Guidance System In at least one implementation, a "time management guidance system" based on visitors' expected departure times will be implemented. Visitors will set time constraints such as their expected departure time, last train time, parking lot closing time, and drop-off / pick-up time using a dedicated app or at the entrance gate upon entry or during their maze experience. The AI ​​will comprehensively analyze this time information along with the visitor's current location, speed of movement within the maze, and past behavior patterns, and provide gradual time warnings at 30 minutes, 15 minutes, and 5 minutes before the set time. For example, if a visitor scheduled to leave at 18:00 arrives at 17:30, a message will appear on their smartphone saying, "Thank you for your hard work. You have 30 minutes until your departure time. Would you like us to guide you to the shortest route to the exit?" The system will integrate multiple time management algorithms and implement machine learning-based individual behavior prediction, real-time traffic information integration, and group coordination functions. For individual behavior prediction, the system learns average movement speed (e.g., 50m per minute), photo-taking time (e.g., average 2.3 minutes per location), and rest frequency (e.g., 5 minutes every 30 minutes) from past visits of five or more times, and calculates individual time allocation. For traffic information integration, it obtains real-time operation information via APIs from JR East, private railway companies, and bus companies, and updates delay and cancellation information every 15 minutes. For example, if the planned 19:15 train is delayed by 20 minutes, it suggests, "You now have 20 minutes of buffer time. How about adding the 'Seasonal Illumination' experience?" For group coordination, it calculates the optimal solution for members with different return times and presents a coordination proposal such as, "We propose a unified schedule where everyone returns at 19:15, with the father set to 21:00, the mother to 19:30, and the child to 20:00." As an emergency response, it offers an "immediate exit mode" for sudden errands or illness, calculating an exit route within 3 minutes from the current location and automatically arranging staff guidance.

[0103] Public transportation integration system The aforementioned time management guidance system integrates with public transport operation information in real time to provide more precise time management. If visitors have pre-registered their nearest station and route, the system automatically acquires train delay information, cancellation information, congestion status, etc., and immediately notifies them if it affects their return route. For example, if a visitor scheduled to take the 19:15 train is delayed by 15 minutes, the system will notify them with a message such as, "Your scheduled train is delayed. You can enjoy the maze a little longer," and suggest an extended experience option. Conversely, if a cancellation or significant delay occurs, the system will provide emergency information on alternative transportation and urge immediate exit from the maze. As a transportation information integration platform, it integrates the ODPT (Open Data Platform for Public Transport) APIs of various railway companies, the Google Transit API, and the operation information APIs of bus companies, covering major transportation systems in all 47 prefectures of Japan. The delay prediction AI learns patterns from the past three years of operation data, such as "the Yamanote Line inner loop is delayed by an average of 3.2 minutes between 18:00 and 19:00 on weekdays," and performs probabilistic delay prediction. For congestion information, the system integrates with congestion sensor data from various railway companies to provide detailed information such as, "The 19:30 departure is expected to be 150% crowded, and the 19:45 departure is expected to be 120% crowded, making it highly likely to secure a seat." For alternative route suggestions, it integrates APIs from Google Maps, Yahoo! Transit, and Ekispert to present up to five alternative routes in order of travel time. In case of disaster, it obtains emergency service suspension information within 30 seconds from JR East's JR-EAST app and Tokyo Metro's API, and supports the immediate arrangement of alternative transportation through integration with taxi dispatch apps (e.g., GO, S.RIDE). To improve location accuracy, it uses indoor positioning beacons (with accuracy within 3m) to determine the precise current location within a maze and calculates the walking time to the nearest exit in seconds.

[0104] Group time adjustment system The system also handles complex time adjustments when groups participate. If different return times are set within a family or group, it provides a function to adjust the overall activity based on the earliest return time. For example, if the father is scheduled to return home at 9:00 PM from a company drinking party, the mother is scheduled to return home at 7:30 PM from an extracurricular activity, and the children have school the next day and are scheduled to go to bed at 8:00 PM, the system sets 7:30 PM as the baseline time and adjusts the route so that everyone can finish the maze around 7:00 PM. Furthermore, if the group splits up midway, it provides individual guidance according to the time constraints of each subgroup and automatically adjusts the final reunion point and time. A group dynamics analysis engine implements optimization algorithms for each family structure pattern (nuclear family, three-generation, single-parent, etc.). The time constraint matrix evaluates the importance of each member's constraints on a 5-point scale, automatically calculating priorities, for example, "Children's bedtime: importance 5, Father's drinking party: importance 3." Distributed activity management allows for simultaneous location tracking of up to 8 people using IoT beacons (with privacy considerations). The meeting point optimization feature calculates equidistant points from each member's current location and proposes three optimal meeting points, taking congestion into consideration. As a real-time adjustment function, it recalculates the remaining members' action plans within 5 minutes if one member's schedule changes (e.g., sudden overtime). For group communication support, it provides member-to-member chat, location sharing, and emergency meeting alarm functions, and also implements a real-time translation function (supporting 50 languages) for members with different language proficiencies (e.g., foreign families). For child safety, it integrates an automatic alert if a child is more than 50 meters away from their guardian, and an emergency location tracking function in case of a lost child.

[0105] Flexible time customization feature The system also incorporates a buffer time setting function, allowing for customization to suit the personality and behavioral characteristics of visitors. For impatient people, there is a "buffer mode" that sets the departure time 30 minutes earlier than the actual departure time; for those who want to enjoy themselves to the very last minute, there is a "limit mode" that calculates the shortest possible departure time; and for first-time visitors, there is a "safe mode" that anticipates them getting lost. Furthermore, the system learns from past visit history, such as a person's movement speed, decision-making time, and photo-taking time, and automatically calculates a time allocation optimized for that individual. For example, visitors who always take many photos will be given an earlier departure guidance, taking into account the time spent taking photos. The behavioral characteristics analysis AI builds an individual's "time perception profile" from past history data, quantifying movement speed (average, fastest, slowest), decision-making time (from presentation of options to decision), photo-taking patterns (frequency, time per photo), and rest habits (frequency, duration). Personality analysis uses a 5-factor model (openness, conscientiousness, extraversion, agreeableness, neuroticism) to predict behavior, and adjustments are made, for example, "High neuroticism: recommend early guidance" and "High openness: proactively suggest new courses." The learning algorithm improves prediction accuracy with each visit, achieving 30% accuracy on the first visit, 70% on the fifth visit, and 90% on the tenth visit or more. Customizable settings include "Free time: adjustable from 15 to 60 minutes," "Guidance timing: adjustable from 3 to 10 visits," and "Guidance method: selectable from voice, text, or vibration." Presets are also available for special cases, such as "Anniversary mode (enjoy without worrying about time)," "Business mode (strict adherence to schedule)," and "Sightseeing mode (emphasis on photography)." Through continuous machine learning, dynamic adjustments are made to account for seasonal variations (slower travel in summer, etc.) and time-of-day variations (increased photography in the evening, etc.).

[0106] Emergency response function The aforementioned time management guidance system also includes emergency response functions. If a visitor significantly exceeds the set time or needs to leave early due to an unexpected matter, an "emergency exit mode" can be activated. In this mode, the system instantly calculates the shortest route from the current location to the exit, temporarily opens maze walls, and arranges for direct guidance from staff. In the case of illness or an emergency, it also works with medical staff to support a safe exit. Furthermore, it has a function to quickly locate visitors who have gotten lost in the maze, and if there is no progress even after significantly exceeding the set time, a notification is automatically sent to staff. The emergency severity determination AI automatically classifies situations into three stages: "minor (schedule change)," "moderate (illness)," and "serious (medical emergency)," and determines the appropriate response protocol. For shortest route calculation, the Dijkstra algorithm and real-time congestion data are combined to calculate the actual fastest route, not just the theoretically shortest, within 3 seconds. The wall opening system uses electrically operated sliding walls (installed in 48 locations) to open "emergency-only passages" that do not normally exist within 5 minutes. The automated staff dispatch system uses GPS location information to dispatch the nearest available staff (up to 15) to the scene within 30 seconds. For medical collaboration, three staff members with nursing qualifications are stationed permanently, optimizing the placement of AEDs, wheelchairs, and stretchers. The lost person detection algorithm triggers phased alerts based on conditions such as staying in the same area for 10 minutes, no progress for 30 minutes, and exceeding a set time of 60 minutes. For communication with visitors, multilingual voice guidance (20 languages), sign language interpreters, and writing boards are provided. Post-incident analysis involves analyzing emergency patterns to continuously improve preventative measures and implement recurrence prevention strategies.

[0107] Seasonal and weather-adaptive features The system also provides special time considerations tailored to the season and time of year. During the year-end and New Year's holiday rush, the summer vacation travel season, and in severe weather such as typhoons, it will provide earlier departure instructions than usual. It also combines information on the visitor's place of residence with weather information and issues advance warnings if bad weather is expected on the return journey. For group use by schools and companies, a centralized management function is provided that matches the meeting and departure times, allowing group leaders to monitor everyone's progress and adjust so that everyone can complete the maze within the scheduled time. This provides peace of mind, allowing participants to enjoy the maze experience without worrying about time while ensuring they leave within the scheduled time. The weather integration system integrates APIs from the Japan Meteorological Agency and private weather companies (Weather News, Japan Weather Association) to obtain detailed hourly forecasts, warnings and advisories, rain cloud radar, and typhoon track forecasts. For traffic impact prediction, machine learning is used on weather data from the past 10 years and the history of transportation service disruptions to build prediction models such as "a 30% probability of delays on the Keihin-Tohoku Line when rainfall exceeds 20 mm / h". As part of regional support, the system predicts weather conditions for the return journey based on the visitor's place of residence (GPS, postal code registration), providing individual guidance such as, "Snow is forecast for the Saitama area from around 7 PM; early departure is recommended." For seasonal event coordination, it considers school holiday calendars, company holiday schedules, and local festival dates, and adjusts schedules to account for expected crowds and traffic congestion. The group management function provides a dedicated dashboard for group leaders, allowing real-time monitoring of the location, progress, and health status of all members, and also offers an automatic follow-up function for members who are falling behind. For emergency coordination, it implements a protocol for mass departure when a natural disaster warning is issued, and also has functions to automatically guide people to higher ground during tsunami warnings and provide safe route guidance during landslide warnings.

[0108] Collaborative Dungeon System In at least one implementation, a "collaborative dungeon system" will be introduced to encourage cooperative play among multiple visitors. Specific areas within the maze will feature high-difficulty "dungeon areas" that are difficult to complete alone, offering special puzzles and challenges that can only be cleared through the cooperation of multiple people (usually 3-6). When visitors encounter other participants within the maze, the AI ​​will automatically propose cooperative play, and if an agreement is reached, they will be granted the right to participate in the dungeon challenge. Within the dungeon, each member will take on a different role (leader, supporter, puzzle analyst, item manager, etc.), and the challenges will be cleared through cooperation that utilizes each member's strengths. Upon success, all members will be awarded a special "master key," which can be used to access hidden doors and secret areas within the maze, receive benefits at other attractions, and obtain limited-edition merchandise. The team-building AI comprehensively analyzes visitor attributes (age, gender, language, visit history), skill assessments (logical thinking, creativity, leadership, cooperativeness), and personality assessments (5-factor analysis of extroversion, cooperativeness, etc.) to calculate the optimal team composition. For example, it automatically suggests patterns such as "family collaboration type with 2 adults and 2 children," "international exchange type with 4 people from different nationalities," and "mentor type with 2 beginners and 2 experienced players." Dynamic difficulty adjustment considers the team's average skill level, age composition, and the presence or absence of language barriers to adjust the puzzle-solving difficulty in 10 levels in real time. For collaborative task design, it offers over 50 patterns of complex tasks requiring diverse skills, such as "Ancient Ruins Mystery: one person deciphers ancient script, one manipulates physical puzzles, one performs mathematical calculations, and one integrates the results." Communication support provides real-time multilingual translation (supporting 30 languages), visual gesture guidance, and written communication support to eliminate language barriers. The performance evaluation system quantitatively assesses the time taken to complete tasks, the originality of creative solutions, and the degree of teamwork, providing feedback by quantifying the degree of individual skill improvement and team contribution.

[0109] AI Team Formation Optimization In the aforementioned collaborative dungeon system, the AI ​​analyzes the attributes, skill levels, languages, and age groups of visitors and automatically suggests the optimal team composition. For example, by combining adults skilled in puzzle-solving, physically fit young people, and creative children in a balanced way, it promotes problem-solving from diverse perspectives. In addition, to facilitate smooth communication even among people meeting for the first time, the AI ​​assistant provides icebreaking questions and common topics to support team building. For participants with different languages, a real-time translation function supports smooth communication and provides an international exchange experience. Furthermore, for less sociable visitors and shy children, consideration is given to gradually getting used to cooperative play through gradual progression (starting with 2 people, then 3 people, etc.). The attribute analysis engine integrates and analyzes basic information upon entry (age, gender, place of residence, language), behavioral history (past cooperative performance, number of times leadership was demonstrated), personality traits (Myers-Briggs personality test, Enneagram analysis), and learning style (visual, auditory, kinesthetic). Skill assessment evaluates decision-making speed within a maze, problem-solving approach, frequency of supporting others, and creative thinking ability on a 5-point scale to construct a comprehensive skill profile. The optimal team formation algorithm combines genetic algorithms and neural networks to calculate the optimal solution from over 100,000 combinations in under 3 seconds. Compatibility analysis learns patterns from past collaboration success rate data, such as "the combination of introverts and extroverts improves satisfaction by 18%." Cultural considerations take into account religious restrictions (such as gender segregation requests), dietary restrictions, and taboos to thoroughly avoid trouble. Team building support uses a topic-generating AI to create natural conversation starters, such as discovering common hobbies, proximity of hometowns, and introductions of children of similar ages. Language support implements real-time translation with speech recognition accuracy of over 95%, explanations of cultural differences in gestures and body language, and nonverbal communication assistance functions.

[0110] Master Key Rarity System Multiple types and rarities are set for the master keys obtained in the system, and different keys are awarded according to the difficulty of cooperation, the number of participants, and the achievements achieved. The "Bronze Key" is obtained when the basic cooperation of three people is cleared, the "Silver Key" is for intermediate cooperation of 4-5 people, the "Gold Key" is for high-difficulty cooperation of 6 or more people, the "Platinum Key" is for a perfect clear within the limited time, and the "Diamond Key" can be obtained under special conditions such as successful cooperation among all members who meet for the first time. Each key can access different levels of hidden areas in the maze, and the higher the rarity of the key, the more valuable rewards and experiences can be obtained. In addition, a "Key Combination System" is introduced where further special areas are unlocked by combining multiple keys, promoting information exchange and repeated cooperation among visitors. In the rarity determination algorithm, the number of cooperative people (3-8 people), age diversity (maximum age difference), language diversity (number of languages used), first-time cooperation rate (ratio of first-time meeting members), clearance time (compared with the target time), and creative resolution (originality score) are comprehensively evaluated and scored out of 100 points. As the acquisition conditions for each rarity, Bronze: 60-69 points, Silver: 70-79 points, Gold: 80-89 points, Platinum: 90-95 points, Diamond: 96-100 points are set. In the hidden area design, five levels of areas corresponding to each rarity are prepared, such as "Bronze Area: Basic Premium Shop", "Silver Area: Guided Tour of Limited Goods Workshop", "Gold Area: Special Cooking Demonstration by Chef", "Platinum Area: VIP Exclusive Lounge", "Diamond Area: Limited Exchange Meeting for Development Team", etc. are provided. In the key combination, new areas are unlocked by combining different rarities, for example, "Gold × Silver × Bronze = Treasure Hunting Area", "Platinum × Platinum = Dialogue Area with Designer", etc. are implemented. In digital asset management, the authenticity of the key is guaranteed by NFT blockchain technology, supporting resale prevention and legitimate exchanges among visitors.

[0111] Diverse Issue Integration System The aforementioned dungeon area features a combination of diverse challenges, including physical puzzles, digital puzzles, physical challenges, and creative activities. For example, "The Mystery of the Ancient Ruins" requires teamwork, with one person deciphering ancient script, another manipulating physical puzzles, a third performing mathematical calculations, and the remaining members integrating the results to decipher the final code. "The Magic Laboratory" presents challenges that comprehensively utilize knowledge of chemical reactions, color combinations, and musical rhythm. Time-limited challenges test quick decision-making and communication skills, and building trust among members is also a crucial element. These challenges are dynamically adjusted by AI based on visitor attributes and past performance to maintain an appropriate difficulty level. The challenge design framework has developed over 50 patterns of comprehensive challenges integrating eight intelligence domains based on Gardner's theory of multiple intelligences (linguistic, logical-mathematical, spatial, kinetic, musical, interpersonal, reflective, and natural inquiry). For physical challenges, the system implements precise operation judgment using high-precision sensors such as puzzle pieces with built-in MEMS sensors, pressure-sensing levers, and tilt angle detection stands. For digital challenges, it provides 3D puzzle solving using AR / VR headsets, 3D puzzles using hologram projection, and an intuitive operation interface using gesture recognition. For physical challenges, it implements accurate motion judgment using motion capture, exercise load adjustment using heart rate monitoring, and coordinated exercise tasks requiring teamwork. For creative activities, it offers collaborative art production in conjunction with AI image generation, improvisational performance using an AI music accompaniment system, and real-time modeling using a 3D printer. The difficulty adjustment AI takes into account each member's strengths and weaknesses, past performance, current fatigue level, and time constraints, and implements a function to dynamically select the optimal level from 10 difficulty levels every 3 seconds.

[0112] Support for building lasting relationships The aforementioned system also incorporates an "Adventure Buddy System" to support the building of ongoing relationships after cooperative play. Members who clear a dungeon together can register as "Adventure Buddies" if they wish, and can team up again on their next visit. The system also provides features that allow buddies to participate in special challenges together and check each other's progress. Furthermore, groups that demonstrate excellent teamwork will be awarded the title of "Legendary Team," and will be featured on the ranking board within the maze and invited to special events. This system provides continuous enjoyment that doesn't end with a one-time experience, and opportunities to build new friendships, thereby increasing the repeat visitor rate and acquiring new customers through word of mouth. The buddy matching system integrates and analyzes communication frequency during cooperative play, mutual evaluation scores, contribution to problem solving, and emotional compatibility (favorability judgment based on facial recognition) to calculate a buddy compatibility score out of 100 points. For ongoing relationship management, the system provides regular online challenge distribution between buddies, event information notifications based on common interests, and automatic reminders for anniversaries (cooperative anniversaries, etc.). The group evaluation system assesses five aspects: task completion time, creativity, teamwork, problem-solving ability, and leadership. Groups with an overall score of 95 or higher are certified as "Legendary Teams." The rewards system offers VIP treatment to Legendary Teams, including exclusive experience tours, meet-and-greets with the development team, beta testing of new areas, and the right to create special merchandise. Social media integration allows for sharing memories between buddies, posting collaborative achievements, and facilitating interaction with other buddy teams. Privacy protection includes features that support the safe and healthy relationship building process, such as the option to choose whether or not to disclose real names, gradual permission settings for exchanging contact information, and a parental consent system for minors.

[0113] Smart Power Management Platform In at least one embodiment, a "smart power management system" will be implemented to monitor the battery status of mobile devices used by visitors and support power management. The system will monitor the battery level of visitors' devices such as smartphones, smartwatches, and tablets in real time, analyze current usage patterns and estimated time spent in the maze, and calculate the estimated time of battery depletion. It will display gradual warnings at 30%, 20%, and 10% battery levels, providing specific information such as, "Based on your current battery level, your device is expected to run out of power around 2:30 PM. The nearest charging station is a 2-minute walk away." It will also include features to extend battery life, such as suggesting power-saving modes, temporarily suspending unnecessary functions, and automatically adjusting screen brightness. The battery monitoring system uses the Bluetooth Low Energy (BLE) protocol to perform device-to-device communication at minimum power, obtaining battery level, charging status, and power consumption patterns from the iOS / Android Battery API. The prediction algorithm analyzes the past 24 hours of usage history, current app usage, screen brightness, wireless communication status, and background processing load using machine learning to predict remaining time with an error of ±5%. Power saving optimization dynamically adjusts 12 items, including CPU clock control, background app restrictions, location information acquisition frequency adjustment, automatic screen off time reduction, and push notification restrictions. Charging station guidance displays a list of 20 charging points (wireless, USB-C, and Lightning compatible) within the maze, showing their location, congestion status, and charging speed, and provides AR guidance to the optimal charging point. Emergency backup activates "Emergency Mode" when the battery level drops below 5%, maintaining location transmission, emergency contact, and staff call functions for up to 3 hours. Power efficiency improvement achieves high-speed, low-power communication through the maze's Wi-Fi 6E environment and implements a function that reduces battery consumption by 40% through automatic switching from 5G communication.

[0114] Strategic Charging Station Placement The aforementioned smart power management system provides optimal guidance to charging stations strategically placed within the maze. Each charging station is equipped with a variety of charging ports, including wireless charging pads, USB-C, Lightning, and Micro-USB, allowing for simultaneous charging of multiple devices. The AI ​​comprehensively assesses the visitor's current location, battery level, congestion at each charging station, and charging speed to guide them to the most efficient charging location. For example, it might present options such as, "Charging station A currently has 3 people waiting, with an estimated wait time of 15 minutes. Charging station B is available, but it will take 5 minutes to reach. Which would you prefer?" For fast-charging compatible devices, priority guidance to the appropriate fast-charging facility is also provided. In designing the charging infrastructure, power load distribution across the entire maze is considered, and each station is equipped with a 15kW fast charger, a Qi wireless charging pad (maximum 15W), and a USB PD compatible port (maximum 100W). For location optimization, visitor behavior patterns are analyzed to prioritize placement in areas where visitors tend to stay longer (puzzle-solving points, rest areas, and scenic spots). The congestion prediction AI learns usage patterns by time of day to make predictions such as "There is a 60% probability that Area B charging stations will be crowded between 2 PM and 4 PM on weekdays." Waiting time optimization automates the calculation of the estimated charging completion time, completion notifications to users currently charging, and preparation guidance for the next user. Charging efficiency management implements automatic selection of the optimal charging profile for each device type and battery capacity, adjustment of charging speed based on temperature monitoring, and an automatic stop function when fully charged. Usage status analysis monitors the operating rate, average charging time, and failure frequency of each charging station in real time to optimize maintenance. Alternative guidance provides information on nearby attractions while waiting to charge, recalculates the maze route according to the charging completion time, and provides a function to coordinate meeting times with group members.

[0115] Entertainment to use while charging The system incorporates a "charge time entertainment" function to make effective use of the waiting time while charging. Around the charging station, there will be puzzle-solving activities that can be enjoyed while seated, mini-games using tablets, a space for interaction with other visitors, and displays of hints for navigating the maze. The AI ​​calculates the charging speed and required amount of charge for the visitor's device and suggests activities appropriate to the time, such as, "Charging will be complete in about 20 minutes. How about trying the 'Ancient Script Deciphering Challenge' during this time?" It is also possible to watch live video of events happening in other areas of the maze or view preview information for the next area to be visited while charging. A mechanism will also be introduced to reliably notify users when charging is complete through device vibration, voice notification, and flashing lights in the surrounding area. The charging time prediction algorithm comprehensively analyzes the device's battery capacity, current remaining charge, charger output, and battery degradation status to calculate the completion time with an accuracy of ±3 minutes. Activity matching combines the estimated charging time (four categories: 5 minutes / 15 minutes / 30 minutes / 60 minutes) with the visitor's areas of interest (puzzles, games, learning, socializing) to automatically select the most suitable content. For mini-game development, we created 20 types of games in each of four categories: "5-minute puzzle-solving," "15-minute cooperative quiz," "30-minute creative workshop," and "60-minute in-depth learning program." The live streaming system implements real-time video streaming from 360-degree cameras installed at 12 locations within the maze, automatic editing of highlights by AI, and a video switching function based on visitor requests. The learning content provides educational elements such as the history of the maze, the design philosophy, explanations of hidden mechanisms, and tutorials on how to beat it. The notification system implements advance notification 5 minutes before charging is complete, multiple notifications upon completion (voice, vibration, light, app notification), and prompts to select whether to continue or stop charging. To promote social interaction, we provide a chat function for visitors charging simultaneously, a matching function for people with common interests, and a function to guide cooperative play after charging is complete.

[0116] Emergency device support The system also includes an emergency response function in case a device's power completely fails. Visitors whose batteries run out will be provided with emergency loaner devices (simple smartphones or GPS-equipped wristbands) that allow them to continue using basic functions such as maze navigation, emergency contact, and staff calling. In addition, emergency information boards (digital signage) installed throughout the maze will constantly display information for visitors with dead batteries (nearest charging station, route to exit, emergency contact information, etc.). Furthermore, alternative means such as a "buddy system" that temporarily links with a companion's device to share information, and simple navigation using QR code (registered trademark) scanning are also provided. Emergency loaner devices include a dedicated smartphone capable of continuous operation for 10 hours (50 units available), a GPS-equipped wristband that operates for 7 days (100 units available), and a solar-powered emergency communication device (30 units available). Device management includes an automatic disinfection system (UV-C irradiation), GPS tracking to prevent loss, and a user registration system (deposit of 1,000 yen). The emergency guidance system displays the shortest route from the current location to each facility, estimated travel time, and congestion status in real time on 25 32-inch 4K displays within the maze. Multilingual support includes automatic language detection via voice recognition, automatic translation display in 20 languages, and non-verbal guidance using pictograms. The Buddy Link system provides short-range device communication via Bluetooth Mesh network, location information sharing, and an automatic SOS broadcast function in emergencies. QR code guidance features QR codes placed at 200 locations within the maze, allowing users to check their current location, set destinations, and display static routes offline. Staff collaboration includes automatic staff notification when emergency devices are lent out, a continuous monitoring system, immediate on-site support in case of problems, and a system for verifying device functionality upon return.

[0117] Preventive power management The aforementioned smart power management system also includes a proactive battery management function. It analyzes visitors' past visit history, device usage patterns, and predicted behavior within the maze, and displays a pre-warning at the time of entry, such as, "Your estimated stay time today is 3 hours, and with your current battery level, you may run out of battery in 2 hours and 30 minutes. We recommend charging before entering or using the charging station immediately after entering." It also provides an estimate of the battery level needed to fully enjoy the maze experience (e.g., "80% or more recommended for a full experience"). Furthermore, to improve charging efficiency, it automatically suggests optimizations such as temporarily pausing unused Bluetooth and Wi-Fi functions, automatically closing unnecessary apps, and setting power-saving settings for the camera flash, providing an environment where visitors can concentrate on the maze experience without worrying about technology. The predictive analytics engine integrates and analyzes individual past data (average stay time, app usage frequency, number of photos taken, charging patterns) and statistical data (seasonal stay time, impact of congestion, extension rate during events) using machine learning. Battery consumption prediction calculates hourly consumption with ±5% accuracy by comprehensively considering GPS usage time, camera shooting frequency, application usage patterns, screen brightness settings, and communication status. Pre-optimization includes automatic execution of a pre-entry checklist (OS update check, closing unnecessary apps, applying power saving settings), individual calculation of recommended charging levels, and suggestion of alternative plans. Real-time optimization includes checking battery status every 10 minutes, suggesting dynamic adjustments to usage patterns, and suggesting power-efficient application alternatives. Emergency measures include activating "Essential Mode" when the battery level is below 15%, continuing operation only for the most important functions (location information, emergency contact), and controlling the gradual shutdown of other functions. The learning function provides continuous learning of individual behavior patterns, improved prediction accuracy, and automatic generation of customized power saving profiles.

[0118] Cross-device data inheritance In at least one embodiment, a "cross-device data transfer system" will be implemented to enable seamless data transfer between visitors' personal devices and facility-provided devices. If a visitor's personal smartphone battery runs low, scanning an encrypted QR code (registered trademark) generated by a dedicated app will instantly transfer all progress data, acquired items, clear history, settings, etc., to a rental smartphone or tablet within the maze. This QR code (registered trademark) contains a visitor-specific encryption key, ensuring security while enabling rapid data transfer. On the rental device, the same functionality and customized interface as the personal device are immediately restored, allowing for a continuous maze experience. Furthermore, at the end of the experience, a new QR code (registered trademark) can be generated, making it easy to retrieve data back to the personal device. The data encryption system protects user data with AES-256 encryption and performs secure key exchange using RSA-4096 public-key cryptography. The QR code (registered trademark) generation stores 4096 bits of information, including a one-time token valid only once, a timestamp (valid for 5 minutes), a device-specific ID, and an encrypted data hash. Data synchronization comprehensively transfers progress (current location, cleared areas, points earned), settings (language, difficulty, exclusion settings, notification settings), cooperative play history (partner information, team performance), and personal records (best time, special achievements, photos / videos). For loaner device management, 50 dedicated tablets (equivalent to iPad® Pro) are always available, with data recovery within 30 seconds, automatic application of personal UI themes, and shortcut settings based on past operation history. Security measures include complete data erasure after use (compliant with DoD 5220.22-M standard), detection of unauthorized access, and automatic lock function in case of abnormal operation. Privacy protection provides prevention of fraudulent access by third parties, identity verification using biometric authentication, and data sharing control functions among family members.

[0119] Personal Adventure Profile At the core of the aforementioned data inheritance system is a cloud-based "Personal Adventure Profile." This profile securely stores encrypted data such as the visitor's maze completion history, cleared dungeon information, acquired master keys and items, selected character class, cooperative play records, personal settings (language, difficulty level, exclusion settings, etc.), and biometric data learning results. The data is distributed and stored across multiple secure cloud servers, ensuring complete data protection even in the event of device failure, loss, or battery depletion. Furthermore, with the visitor's consent, this profile can be used in other attractions within the theme park, providing a consistent RPG experience. Regular automatic backups record progress down to the second, minimizing the risk of data loss. The cloud architecture achieves 99.99% availability through a multi-cloud configuration of AWS / Azure / GCP, and implements disaster recovery through geographical distribution (data centers in Tokyo, Osaka, and Fukuoka). The data structure design employs hierarchical data management in JSON format, high-speed access using a NoSQL database (MongoDB), and efficient data queries using GraphQL. For security, we implement a zero-trust security model, end-to-end encryption, regular security audits (four times a year), and full compliance with GDPR / Personal Data Protection Act. Our backup system achieves real-time synchronization (RPO=0 seconds), automatic incremental backups (three times a day), long-term archiving (7 years), and reduced recovery time (RTO=30 seconds or less). For API integration, we facilitate connection with other systems through a RESTful API design and implement OAuth 2.0 authentication, rate limiting, and API version control. For profile analysis, we implement machine learning-based behavioral pattern recognition, preference prediction, enhanced personalization, and the provision of anonymized statistical data.

[0120] Session continuation and recovery function The system incorporates a "session continuation function," allowing visitors to resume their maze experience from where they left off on their next visit. Upon a visitor's return, their previous adventure profile is automatically loaded via ID authentication at reception (facial recognition, fingerprint authentication, IC card, QR code (registered trademark), etc.). The AI ​​analyzes previously completed dungeons, unfinished quests, owned master keys, and information on cooperative play partners, and then presents continuation options such as, "Last time you cleared up to the 'Ancient Ruins Dungeon.' Would you like to challenge the 'Magic Tower' next? Or would you like to start from a new area?" If time has passed since the previous visit, information on newly added content and updated puzzles is also provided, ensuring a fresh experience for repeat visitors. Session management implements high-speed session storage using Redis Cluster, session state persistence, session sharing across multiple devices, and load balancing using a load balancer. The authentication system offers enhanced identity verification through multi-factor authentication (MFA), biometric authentication (face, fingerprint, iris) with an accuracy of over 99.7%, contactless authentication using IC cards / NFC, and disposable authentication using dynamically generated QR codes (registered trademark). For continuity assessment, it comprehensively evaluates the time elapsed since the last session, update content, and individual learning progress to automatically determine one of three patterns: "full continuation," "partial continuation," or "recommended to start anew." Progression management implements a gradual difficulty increase system, skill growth tracking, weakness overcoming support, and proficiency-based customization. Content update detection automatically extracts newly added puzzles (weekly updates), seasonal event information, and system function enhancement information since the last visit, and guides users with priority based on their individual interests. For data integrity, it implements consistency guarantees across distributed databases, transaction management, race condition resolution, and automatic repair functions to ensure full recovery from interruptions.

[0121] The aforementioned session continuation function also integrates a "progressive difficulty system." It multidimensionally analyzes visitors' past performance, strategy patterns, roles in cooperative play, reaction time, and correct answer rate, and adjusts the difficulty level in stages according to the individual's skill improvement. For example, the first visit starts with basic puzzle solving (targeting an 80% or higher correct answer rate), the second time with slightly more complex logic puzzles (targeting a 70% correct answer rate), the third time with cooperative tasks requiring teamwork (measuring communication frequency), and from the fourth time onward, it progresses to advanced challenges requiring creativity and application skills (evaluating original solutions). In addition, it learns in detail the strengths and weaknesses in specific fields (mathematics, language, spatial reasoning, pattern recognition, etc.) and suggests supplementary problems to reinforce weaknesses (reviewing from the basics in weak areas) and special challenges that utilize strengths (advanced problems in strong areas). The learning curve takes individual differences into account and avoids abrupt increases in difficulty by using an "adaptive difficulty adjustment algorithm" to always provide "just the right challenge" (optimal difficulty level based on flow theory). Long-term visitors are offered special ranks such as "Master," "Legend," and "Grandmaster," which grant them privileges such as the right to act as a mentor for other visitors (earning mentoring points), access to prototype versions of new dungeons, and participation in discussions with the development team. Furthermore, difficulty levels are adjusted to take into account the time of day and physical condition, automatically lowering the difficulty if fatigue accumulates, ensuring an optimal experience at all times.

[0122] The aforementioned data transfer system also includes a complete data recovery function for emergencies. In the event that a personal device is lost, malfunctions, stolen, submerged in water, or completely discharged, making it temporarily inaccessible, complete data recovery is possible through visitor identity verification (multi-factor authentication: biometric authentication + security questions + companion verification + past behavior pattern matching). The recovery process is performed in stages, first immediately restoring basic data (progress, acquired items), and then sequentially restoring detailed data (cooperative play history, custom settings). During this process, multiple security checks, including biometric authentication (combination of fingerprint, vein pattern, iris, and facial recognition), pre-registered security questions (3 questions randomly selected from a maximum of 5), companion identity verification (approval from the companion's device), and past behavior pattern matching (characteristic movement routes, frequently selected options), are used to protect legitimate visitor data while preventing unauthorized access. Furthermore, if a shared account is set up with family or friends, data access by proxy is also possible, and features such as parental control (parental control function) for parents to manage their children's data or family members to support elderly users are also provided. In the event of an emergency recovery, "Safe Mode" will be activated, allowing users to continue their maze experience with minimal functionality. Furthermore, data privacy protection and compliance with international standards such as GDPR are thoroughly implemented, employing military-grade encryption strength (AES-256) to create an environment where visitors can entrust their data with peace of mind. Regular external security audits are also conducted to maintain a defense system against the latest threats.

[0123] In at least one embodiment, a "smart reunion support system" will be implemented for when group members become separated within the maze. The AI ​​will continuously monitor each member's real-time location, movement speed, direction of movement, current progress in the experience, and biometric information such as heart rate, and will automatically determine with high accuracy whether the separation is intentional or accidental. A machine learning model will be used for the determination, comprehensively considering past behavioral patterns (e.g., always preferring to act separately), group relationships (family / friends / first-timers), and current emotional state (enjoying / anxious). If separation is accidental, the system will immediately send a "member separation alert" to the devices of all affected individuals and propose multiple most efficient reunion routes. The calculation of the reunion route will use a "dynamic route optimization algorithm" that considers not only the simple shortest distance, but also each member's movement speed, physical fitness level, progress in the puzzle-solving they are currently working on, and congestion levels. In addition, special effects (e.g., light displays celebrating the reunion, emotional background music) will be prepared at the reunion point to transform the anxiety of separation into an enjoyable experience. If a child gets lost, they will be given top priority, and comprehensive support will be provided, including immediate notification to parents, automatic alerts to the nearest staff, continuous tracking of the child's current location, and voice encouragement ("Mommy will be here soon"). Furthermore, for groups where members frequently get separated, the use of a "buddy system" is suggested, which also provides a function that notifies members with vibrations if they get separated by more than a certain distance.

[0124] At the heart of the aforementioned smart reunion support system is a cloud-based "Personal Adventure Profile." This profile stores highly encrypted data including the visitor's maze completion history, cleared dungeon information, acquired master keys and items, selected character class, cooperative play records, personal settings (language, difficulty level, exclusion settings, etc.), and biometric data learning results. Furthermore,...

Claims

1. An attraction space in which visitors can move around, and a means of performing effects within the said attraction space, Sensor means are placed at multiple locations within the aforementioned attraction space to detect at least one of the visitor's biometric information, behavioral patterns, conversation content / search history, preferences / attribute information, and game skills / operational characteristics. A component having a physical wall or door that is movable by an electric mechanism, and which can change the path configuration within the attraction space by moving the wall or door, Based on the information detected by the aforementioned sensor means, the artificial intelligence determines the route configuration and the movement and exploration behavior of visitors. An AI-controlled attraction performance system characterized by comprising control means for determining or changing the individually optimized performance.

2. The AI-controlled attraction performance system according to claim 1, characterized in that the control means dynamically adjusts the route configuration and performance content based on at least one factor selected from time information, congestion status, visitor attributes, weather, park trends, season, event status, fluctuations in popular spots within the park, SNS posting trends, and surrounding facility status.

3. The AI-controlled attraction performance system according to claim 1, characterized in that the performance control means uses at least one of the following: video projection, sound effects, lighting effects, special effects, environmental control, motion control, scent control, temperature control, airflow control, tactile feedback, and means for integrating and controlling these technologies by artificial intelligence.

4. A means of communication that communicates with terminal devices carried by visitors, Means for providing personalized performance information, services, or content through the aforementioned communication means, The AI-controlled attraction performance system according to claim 1, further comprising the features described above.