Crowd Control via Check-in Time Recommendations
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Solution Overview
Problem
Public transportation stations face overcrowding issues during peak hours, events, and holidays, posing a challenge for crowd management to prevent crushes and optimize passenger distribution.
Innovation Solution
A computer-implemented method for crowd control that recommends check-in times to passengers based on travel information, consumption tendencies, and station capacity, using a system that activates ticket verification devices to manage access and incentivizes passengers with credit points for adhering to recommended times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If passengers arrive at the station during peak hours to catch their trains, then they can ensure timely boarding, but the station becomes overcrowded creating safety risks and reducing service quality
Solution Approach 1:
The system performs preliminary actions by calculating and recommending optimal arrival times for passengers before they reach the station. The crowd management system analyzes historical data, real-time passenger flow, and train schedules to determine the ideal check-in time for each passenger, allowing them to arrive neither too early nor too late, thus avoiding overcrowding while ensuring timely boarding.
Solution Approach 2:
The system dynamically adjusts recommended arrival times based on real-time conditions. As passenger flow patterns change throughout the day and across different routes, the system continuously updates its recommendations to reflect current station conditions, making the crowd management approach adaptive and responsive to changing circumstances.
2Ease of operation
If the station allows free access to all passengers during peak hours, then passenger convenience is maintained, but resource utilization becomes inefficient and overcrowding occurs
Solution Approach 1:
The system changes the temporal parameter of passenger access by introducing time-based recommendations. Instead of uniform access policies, the system assigns specific recommended arrival time windows to different passenger groups based on their routes, travel times, and historical behavior patterns. This temporal segmentation optimizes resource utilization while maintaining operational convenience through digital guidance rather than physical barriers.
Solution Approach 2:
The system implements feedback mechanisms where passenger responses to recommended arrival times are collected and analyzed. This feedback loop allows the system to learn from actual passenger behavior patterns and refine its recommendations, improving both resource utilization efficiency and passenger convenience over time through data-driven optimization.
3Object-affected harmful factors
If the station implements strict crowd control measures to prevent overcrowding, then safety is improved, but passenger flow efficiency and access speed are reduced
Solution Approach 1:
The system performs preliminary crowd distribution by recommending arrival times that spread passengers out before they enter the station. This preliminary temporal distribution prevents the formation of dangerous crowds while maintaining smooth passenger flow, as passengers arrive at optimized intervals rather than all at once during peak hours.
Solution Approach 2:
The system acts as an intermediary between safety requirements and passenger flow efficiency. Rather than implementing direct physical restrictions that would slow passenger access, the system uses digital recommendations and information provision to guide passenger behavior, achieving crowd control objectives while preserving access speed through voluntary compliance with optimized arrival time suggestions.
Data Source
AI summary
Methods, systems, and computer-readable storage media for crowd control based on check-in time recommendations, including operations of receiving, from a plurality of users, travel information, the travel information including, for each of the plurality of users, a user identification, a departure location, and a departure time, determining a total number of passengers within a time interval associated to the departure time from the departure location, generating a recommended check-in time for each of the plurality of users based on the travel information and the total number of passengers, displaying for each of the plurality of users the recommended check-in time, and activating a setting of a ticket verification device to prevent access to a portion of the departure location for each of the plurality of users before the recommended check-in time.