BLE Beacon Wait Time Estimation for Dynamic Queues
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Solution Overview
Problem
Conventional methods for estimating wait time at lines or queues are often inaccurate and cumbersome, relying on historical data and customer input, and fail to provide real-time and precise information, which is inconvenient for users in dynamic public venues like airports and amusement parks.
Innovation Solution
A system utilizing Bluetooth Low Energy (BLE) beacons to detect user presence and movement, estimating wait time by triangulating location and tracking progression through the line, providing real-time updates and recommendations for shorter wait times across multiple lines based on user-specific needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional methods using historical data and crowd sourcing are used to estimate wait time, then the system can provide wait time information, but the accuracy and real-time precision deteriorate due to reliance on outdated data and customer input
Solution Approach 1:
The patent replaces manual customer input mechanisms with automated image recognition and computer vision systems. Cameras capture queue images, and AI algorithms automatically analyze them to determine queue length and wait time, eliminating the need for customers to manually provide data while achieving real-time accuracy.
Solution Approach 2:
The system enables self-monitoring of queue conditions through automated image capture and analysis. The queue management system independently tracks and updates wait time information without requiring customer participation, continuously analyzing captured images to provide real-time queue status.
2Loss of information
If conventional crowd sourcing methods are used, then customer input can be collected, but the ease of operation deteriorates due to cumbersome input requirements
Solution Approach 1:
The system automatically captures and processes queue information without requiring any customer action. Cameras continuously monitor the queue, and the system independently extracts relevant data, completely eliminating the burden of customer input while ensuring complete data collection.
Solution Approach 2:
Manual customer input is replaced with automated optical sensing and image processing systems. The system uses cameras and computer vision algorithms to automatically detect and record queue parameters, substituting mechanical customer actions with automated sensing mechanisms.
3Reliability
If historical data is used for wait time estimation, then the system can provide estimates, but the adaptability to current dynamic situations deteriorates
Solution Approach 1:
The system transitions from static historical data to dynamic real-time image-based measurements. Cameras continuously capture current queue states, and the system dynamically updates wait time estimates based on present conditions, allowing immediate adaptation to changing queue lengths and service speeds.
Solution Approach 2:
The system implements continuous feedback loops where captured images are constantly analyzed to update queue status. This real-time feedback mechanism ensures the system reliably reflects current conditions while adapting to dynamic changes as they occur in the queue environment.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system offers accurate and real-time wait time estimation, enhancing user convenience by providing personalized recommendations, thus improving the overall experience in public venues by optimizing wait time management.
Implementation Method 1
a distance between the user and the BLE beacon may be estimated based on a strength of the BLE signal received at the user's device or at the BLE beacon
Data Source
AI summary
A system or method is provided to estimate wait time at a line or a queue. In particular, the system may estimate the wait time at a line by detecting the presence of a user at the line via Bluetooth Low Energy (BLE) communication. In an embodiment, the system may detect when the user enters the line and when the user departs from the line via BLE beacons and may estimate the wait time at the line based on how long the user is in line. In an embodiment, a grid of multiple BLE beacons may be installed or provided at the location of the line to track the location and movement of a user. The system may determine the wait time for the line based on the location and the movement of the user.