Intelligent Queue Guidance with Predictive Timing to Reduce Wait Times
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Solution Overview
Problem
Existing systems fail to efficiently guide users to join queues at optimal times, leading to inefficient use of time when line sizes vary significantly.
Innovation Solution
A mobile device-based intelligent queueing system that detects queues, monitors their size over time, predicts optimal queuing times, and provides navigation to minimize wait times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If users join queues without guidance systems, then they can access services, but they spend excessive time waiting in line
Solution Approach 1:
The system performs preliminary actions by monitoring queue sizes and predicting future queue lengths before users arrive. It identifies optimal entry times in advance and notifies users beforehand, allowing them to plan their queue joining strategy without actually being in the queue yet. This resolves the contradiction by reducing wait time through advance planning while maintaining simple user interaction.
Solution Approach 2:
The system implements feedback by continuously monitoring actual queue sizes and comparing them with predicted values. This feedback loop allows the system to refine its predictions and provide increasingly accurate optimal entry time recommendations, thereby reducing user wait time while keeping the interface simple through automated notifications.
2Loss of information
If queue sizes are monitored manually, then users can make informed decisions, but the system complexity increases significantly
Solution Approach 1:
The system applies self-service by having mobile devices in the queue area automatically monitor and report their own locations and queue status. Each device contributes to the collective understanding of queue size without requiring centralized manual monitoring. This reduces system complexity while providing comprehensive queue size information to users.
Solution Approach 2:
The system uses an intermediary approach by leveraging existing mobile devices as mediators between users and the queue management system. These devices collect location data and queue size information without requiring dedicated monitoring infrastructure, thereby providing rich information while minimizing system complexity.
3Productivity
If users arrive at queueing locations without optimal timing, then they can access services, but their time efficiency decreases
Solution Approach 1:
The system performs preliminary analysis of queue patterns and predicts optimal entry times before users arrive at the queueing location. By notifying users in advance of the best time to join, it enables them to optimize their time efficiency without actually being present in the queue yet, thereby reducing wait time while improving overall productivity.
Solution Approach 2:
The system applies dynamics by continuously adapting its predictions based on real-time queue size changes and historical patterns. It dynamically adjusts optimal entry time recommendations to match current conditions, ensuring users always receive timely advice that maximizes their time efficiency and minimizes wait time.
Data Source
AI summary
A system and method for intelligent queueing and guidance is disclosed. The system and method can be used to determine when a user should queue and to provide navigation to a queueing location. The system can include a queueing detection and monitoring module, a queue prediction module, a navigation module, and an optimal timing module. The system can be implemented with mobile devices including smart phones, smart watches, and/or other wearable devices.