Dynamic Venue Crowd Distribution via Real-Time Queue Analysis
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Solution Overview
Problem
Large and complex venues face challenges in providing visitors with relevant information in real-time, as existing methods like static maps and general information apps fail to account for dynamic factors such as queue sizes and crowd distribution, leading to inefficient visitor experiences and poor decision-making.
Innovation Solution
A system and method that personalizes itineraries for venue attendees by calculating optimal queue and crowd sizes, dividing attendees into groups based on these metrics, and generating recommendations for points of interest to distribute crowds evenly, thereby optimizing visitor experiences and reducing congestion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If static maps and general information apps are used to provide venue information, then information availability is improved, but information relevance and real-time accuracy deteriorate
Solution Approach 1:
The patent transforms static information delivery into a dynamic system that continuously updates based on real-time venue conditions. The system monitors crowd density, queue lengths, and point of interest status dynamically, then adjusts recommendations in real-time to maintain information relevance while preserving comprehensive availability.
Solution Approach 2:
The system implements feedback loops where user interactions, movement patterns, and venue condition data are continuously collected and processed. This feedback drives the personalization engine to refine recommendations, ensuring information remains both relevant and accurate throughout the visitor experience.
2Ease of operation
If attendees manually plan routes and itineraries using available information, then decision-making autonomy is improved, but time consumption and decision quality deteriorate
Solution Approach 1:
The system enables self-service by automatically generating personalized itineraries based on user preferences, group composition, and real-time venue conditions. Users receive ready-to-follow recommendations without manual planning, yet retain the ability to adjust preferences and receive alternative suggestions, maintaining autonomy while eliminating time-consuming deliberation.
Solution Approach 2:
The system performs preliminary actions by pre-calculating optimal routes and itineraries before users need them. By anticipating user needs and pre-processing venue data, the system delivers ready-made recommendations that save time while allowing users to review and modify plans as desired.
3Quantity of substance
If crowd distribution is not managed, then venue capacity utilization is improved, but visitor experience quality and flow efficiency deteriorate
Solution Approach 1:
The system applies local quality by providing differentiated recommendations to different user groups based on their specific contexts, locations, and preferences. Rather than uniform crowd management, the system tailors guidance to distribute crowds optimally across various points of interest, maintaining high capacity utilization while preventing localized congestion that would reduce overall flow efficiency.
Data Source
AI summary
A platform provides recommendations for points of interest in a venue to venue attendees. Different points of interest are recommended in different amounts in order to prevent congestion in the venue in the form of extremely long queues or extremely large crowds. To achieve this, the platform divides a large group of venue attendees into multiple sub-groups, with each sub-group being recommended a different point of interest, and the size of each sub-group based on a difference between an optimal queue or crowd size and an actual queue or crowd size of a queue or crowd associated with that point of interest.