Guest-Specific AI Entities for Personalized Theme Park Interaction
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Solution Overview
Problem
Existing amusement park systems lack the ability to create complex and customized guest experiences, failing to leverage guest-specific data for personalized interactions.
Innovation Solution
Implementing guest-specific artificial intelligence entities that utilize sensors to collect and analyze guest data, allowing for personalized interactions through park features such as displays, lighting, and sound effects, and enabling AI entities to exist both in the physical and digital environments to enhance immersion.
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 insufficient
Solution Approach 1:
The system segments guest experience customization into modular components: guest activity detection devices collect specific data types, AI entity management system processes and manages multiple AI entities independently, and park features are individually controlled to manifest AI entities. This segmentation enables customized experiences while maintaining manageable system complexity through modular architecture.
Solution Approach 2:
The AI entity management system serves multiple functions: it manages guest-specific AI entities, processes sensor data from various sources, controls diverse park features (displays, lighting, sound), and adapts to different guest preferences. This multi-functionality achieves high adaptability without proportionally increasing system complexity.
2Loss of information
If guest-specific AI entities are implemented, then guest experience personalization is enhanced, but data processing requirements increase
Solution Approach 1:
The system extracts only relevant guest data from sensor inputs using AI activity detection, focusing on specific behaviors and preferences rather than processing all possible data. This selective extraction reduces data processing requirements while maintaining effective guest personalization by concentrating computational resources on meaningful information.
Solution Approach 2:
Guest-specific AI entities autonomously learn from guest activities and self-adjust their behavior patterns without requiring constant external processing. The AI entities independently manage their own adaptation to guest preferences, reducing the computational burden on central systems while maintaining high personalization quality.
3Ease of operation
If AI entities manifest through multiple park features, then guest immersion is enhanced, but system coordination complexity increases
Solution Approach 1:
The system merges control of diverse park features (displays, lighting, sound effects) under a unified AI entity management system. This consolidation enables coordinated manifestation of AI entities across multiple features while simplifying system architecture by providing centralized control, thus enhancing guest immersion without proportionally increasing coordination complexity.
Solution Approach 2:
The AI entity management system acts as an intermediary layer between guest activity detection and park feature control. This intermediary coordinates the manifestation of AI entities across multiple features by translating guest data into appropriate feature activations, simplifying the coordination complexity while enhancing the integrated guest experience.
Data Source
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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.