Carriage Crowding Estimation Using Remaining Carrying Space
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Solution Overview
Problem
Passengers in public transportation, such as subways, often cannot anticipate the crowding level of carriages, leading to inefficient waiting and potential inability to board due to overcrowding.
Innovation Solution
A method using image recognition and sensors to determine the remaining carrying space in a carriage, calculate the recommended number of people that can be accommodated, and estimate the crowding degree, enabling passengers to choose less crowded carriages.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If passengers wait for public transportation without knowing the crowding level, then they can board any carriage, but they waste time waiting and may be unable to board due to overcrowding
Solution Approach 1:
The system performs preliminary detection of the carriage's remaining carrying space using image recognition and sensor data before the passenger arrives. The server pre-calculates and stores the crowding degree information, so that when the passenger queries the system, the information is already prepared and immediately available, eliminating waiting time.
Solution Approach 2:
The patent introduces a server as an intermediary between the carriage's detection devices and the passenger's terminal. The server collects data from image recognition and sensors, calculates the crowding degree, and transmits this information to the passenger's device, enabling the passenger to make informed decisions without directly accessing the carriage's internal systems.
2Productivity
If passengers choose carriages randomly, then they can board quickly without information, but they may board overcrowded carriages and need to wait for the next one
Solution Approach 1:
The system implements feedback by continuously monitoring the carriage's occupancy through image recognition and sensors, calculating the remaining carrying space, and providing real-time crowding degree information to passengers. This feedback loop enables passengers to make informed choices, improving both boarding efficiency and success rate.
Solution Approach 2:
The system pre-calculates the crowding degree before the passenger needs to make a decision. By having the information ready in advance through preliminary detection and calculation, passengers can quickly select appropriate carriages without random guessing, thereby improving boarding efficiency and reliability.
3Measurement precision
If the system uses image recognition and sensors to detect crowding, then passengers can board less crowded carriages, but the system complexity increases
Solution Approach 1:
The patent makes the server perform multiple functions: it not only calculates the crowding degree but also manages data transmission, communicates with various detection devices, and provides information to multiple passengers' terminals. This multi-functionality reduces the need for separate dedicated components for each function, thereby managing system complexity while maintaining high measurement precision.
Solution Approach 2:
The server acts as an intermediary that simplifies the overall system architecture by centralizing the processing and calculation functions. Instead of having complex processing units in each passenger's device or directly in the carriage, the server mediates between the simple detection devices and the passenger terminals, managing the complexity centrally.
Data Source
AI summary
A crowding degree estimation method applied to an electronic device is provided. In the method, the electronic device determines a remaining carrying space of a carriage according to an image viewed from a top of an interior of the carriage, and determines a recommended remaining number of people that can be carried according to the remaining carrying space, the number of people already in the carriage, and a maximum number of people that can be carried of the carriage. The electronic device determines the crowding degree according to the recommended remaining number of people. The method can determine the crowding degree of each carriage of a public transportation and recommend passengers with less crowded carriages to save passengers' waiting time.