Fare Evasion Detection Using Passenger-Device Trajectory Matching
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing tagless or gate-free fare payment methods in public transportation face challenges with reduced payment recognition rates in crowded situations and vulnerability to hacking, leading to fare evasion.
Innovation Solution
A method and apparatus that estimate passenger and IoT device positions and trajectories using image information and wireless signals to match fare-paid devices with passengers, employing a deep learning-based model to detect fare evasion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If tagless or gate-free payment method is used, then ease of operation is improved, but reliability deteriorates due to fare evasion and hacking vulnerability
Solution Approach 1:
The system continuously monitors passenger movements using image recognition and compares them with device location data from wireless signals. This feedback mechanism tracks whether passengers who paid fare actually boarded and remained on the vehicle, providing real-time verification to maintain reliability while preserving the ease of tagless payment operation.
Solution Approach 2:
The patent introduces an intermediary verification system that acts as a mediator between the payment system and the actual fare collection. Image recognition technology and wireless signal tracking serve as intermediaries to verify passenger-device correspondence, ensuring reliable fare collection without requiring traditional tagging or gate mechanisms.
2Measurement precision
If image recognition and wireless signal tracking are implemented, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system employs multi-functional components that serve multiple purposes. For example, wireless signal receivers not only track device locations but also identify passenger movements when combined with image recognition. This multi-functionality reduces the need for separate dedicated devices for each measurement function, thereby limiting the increase in device complexity while maintaining high measurement precision.
Solution Approach 2:
The patent merges image recognition technology with wireless signal tracking into a unified fare verification system. By combining these two measurement approaches, the system achieves higher measurement precision in determining passenger-device correspondence while avoiding the complexity of operating completely separate systems. The merged system processes both visual and signal data through integrated algorithms.
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
Accurately identifies fare-evading passengers, preventing financial loss and ensuring smooth operation of tagless payment systems.
Implementation Method 1
a wireless signal receiving unit receiving wireless signals from the IoT devices and a position estimation unit estimating positions of the IoT devices within the detection area based on the wireless signals
Implementation Method 2
an image information processing unit estimating positions of passengers within the detection area based on image information, the image information being information obtained by capturing the detection area
Data Source
AI summary
A method and an apparatus for detecting fare evasion using image information and wireless signals. According to an embodiment of a present disclosure, a method for detecting fare evasion comprising: estimating positions of passengers within a detection area or trajectories of the passengers within the detection area based on image information, estimating positions of devices within the detection area or trajectories of the devices within the detection area based on wireless signals, determining whether the passengers and the devices match by comparing the positions of the passengers with the positions of the devices or comparing the trajectories of the passengers with the trajectories of the devices and determining fare-evading passengers among the passengers based on the matching result.