Origin Destination Pair Recovery Using Time Interval Analysis
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Solution Overview
Problem
In services that rely on origin/destination pair information, such as public transportation and electronic road pricing, failures due to IC card, POS machine, or communication faults lead to service disruptions, requiring manual intervention, which is inconvenient, especially during peak times.
Innovation Solution
A method and apparatus that automatically identify missing origin/destination points by determining the current and previous operation times and using historical data or location/movement information to predict the missing point, allowing for automated resolution of recording failures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual intervention is used to resolve origin/destination pair recording failures, then service continuity is maintained, but service efficiency and user convenience deteriorate during peak times
Solution Approach 1:
The system automatically identifies and resolves missing origin or destination points using historical data and time interval analysis without requiring manual intervention. The processing circuit autonomously determines the missing point based on stored operation records and current operation context, enabling self-service recovery from recording failures.
Solution Approach 2:
The system pre-stores historical origin/destination pair operation records and uses them proactively to predict and fill missing information before service failure occurs. By analyzing time intervals and comparing with historical patterns, the system prepares corrective actions in advance, preventing service disruption rather than reacting after failure.
2Productivity
If automated identification of missing points is implemented, then service efficiency improves, but system complexity increases
Solution Approach 1:
The system introduces a processing circuit as an intermediary component that mediates between the recording failure and service disruption. This intermediary automatically analyzes time intervals, retrieves historical data, and determines missing points, simplifying the overall system architecture by centralizing the recovery logic in a dedicated component rather than distributing complexity across multiple systems.
3Measurement precision
If historical data and time interval analysis are used to identify missing points, then measurement precision of missing point identification improves, but information processing requirements increase
Solution Approach 1:
The system applies local quality by focusing data analysis on specific relevant parameters rather than processing all available data. It specifically examines time intervals between operations and compares only the necessary historical records related to the current operation context, thereby achieving high identification accuracy while minimizing overall data processing volume.
Data Source
AI summary
The present disclosure relates to identifying an origin/destination pair. Aspects include identifying an origin/destination pair in a service, which includes determining a current time when the current operation is executed in response to failure of a current operation for recording an origin/destination pair. Aspects also include determining a previous time when a last operation was executed for recording an origin/destination pair and identifying a missing point causing failure of the current operation based on a time interval between the current time and the previous time.