Guest-Specific AI Entity Control for Personalized Park Experiences
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Solution Overview
Problem
Existing amusement park systems lack the ability to create complex and customized guest experiences, limiting the enhancement of guest interaction and immersion.
Innovation Solution
A system that utilizes guest activity detection devices to collect data, an AI entity management system to analyze this data, and park features to modify guest experiences based on guest-specific AI entities, creating personalized interactions and simulations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional amusement park systems are used, then system simplicity is maintained, but guest experience customization capability is limited
Solution Approach 1:
The system segments the amusement park experience into multiple independent AI entities, each responsible for specific guest interactions. Guest activity detection devices are distributed throughout the park, and AI entities are created individually for each guest rather than using a monolithic system, enabling customization without requiring complete system redesign for each guest
Solution Approach 2:
The AI entity management system serves multiple functions: it creates AI entities, manages their properties, coordinates park features, and processes guest activity data. Park features are designed to be universally controllable by AI entities through standardized interfaces, allowing the same infrastructure to support diverse personalized experiences
2Loss of information
If guest activity detection devices are deployed, then guest behavior data collection is improved, but system complexity and data processing requirements increase
Solution Approach 1:
The AI entity management system acts as an intermediary between guest activity detection devices and AI entities. It aggregates raw detection data, processes it into meaningful behavioral patterns, and uses this information to modify AI entity properties. This intermediary layer simplifies the data flow by centralizing processing logic and preventing direct complex interactions between multiple detection devices and individual AI entities
Solution Approach 2:
The system implements continuous feedback loops where guest activity detection devices monitor guest behavior, the AI entity management system analyzes this data in real-time, and AI entities dynamically adjust their properties based on detected patterns. This feedback mechanism enables adaptive personalization without requiring manual intervention or complex pre-programming
3Adaptability or versatility
If AI entities dynamically modify park features, then guest experience personalization is enhanced, but control system complexity increases
Solution Approach 1:
The system enables dynamic modification of park features through AI entities whose properties change in real-time based on guest behavior. Park features are designed with adjustable parameters that can be dynamically controlled by AI entities, allowing the system to adapt to different guest preferences and behaviors without requiring physical reconfiguration or manual intervention
Solution Approach 2:
The AI entity management system serves as a mediating control layer between AI entities and park features. It translates AI entity decisions into standardized control commands for park features, managing the complexity of coordinating multiple features simultaneously while providing a simplified interface for AI entities to request modifications
Data Source
AI summary
Systems and methods presented herein include guest activity detection devices configured to detect activity of guests of an amusement park, and to send data indicative of the detected activity; an artificial intelligence entity management system configured to analyze the data indicative of the activity of the guests, and to modify properties of guest-specific artificial intelligence entities based at least in part on the analyzed data indicative of the activity of the guests; and park features disposed within a physical environment of the amusement park and configured to be instructed by the guest-specific artificial intelligence entities to modify a guest experience for the guests of the amusement park in accordance with the properties of the guest-specific artificial intelligence entities.