Fuel Pump Data Evaluation for Alarm Detection
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Solution Overview
Problem
Fuel providers face challenges in detecting and resolving issues with self-service fuel pumps, such as reduced fuel output and payment system failures, which can lead to customer dissatisfaction due to the lack of efficient monitoring and alert systems.
Innovation Solution
A system and method for evaluating fuel pump data by receiving and updating information on fuel pump performance, detecting alarm conditions based on thresholds, and generating alerts to notify users of potential issues, including monitoring the elapsed time for resolution of alerts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If fuel providers manually monitor fuel pump functionality, then customer service quality may be maintained, but detection speed and resolution efficiency of issues are reduced
Solution Approach 1:
The system implements continuous feedback loops where fuel pump data is automatically collected, analyzed, and used to trigger alerts. The processor receives fuel pump information, compares it against thresholds, and provides feedback through alerts when alarm conditions are detected, enabling rapid response without manual intervention.
Solution Approach 2:
The monitoring system operates autonomously to detect and alert about fuel pump issues. The system self-monitors fuel pump performance metrics, automatically updates previous information, and generates alerts without requiring fuel provider intervention, thereby reducing detection time while maintaining reliability.
2Difficulty of detecting and measuring
If comprehensive fuel pump monitoring is implemented, then issue detection capability is improved, but system complexity increases
Solution Approach 1:
The system extracts only the critical fuel pump metrics that indicate potential issues (such as flow rate, transaction cancellations, help button presses, card read errors, and printer errors). By focusing on these specific parameters rather than monitoring all possible fuel pump data, the system achieves comprehensive issue detection while maintaining manageable complexity.
Solution Approach 2:
The system monitors multiple parameters simultaneously (flow rate, transaction cancellations, help button presses, card read errors, printer errors) and changes their representation into a unified alarm condition assessment. The processor evaluates these parameters against thresholds to determine alarm conditions, transforming complex multi-parameter monitoring into a simplified decision framework.
3Productivity
If real-time fuel pump data collection is performed, then customer satisfaction is improved through faster issue resolution, but data processing requirements increase
Solution Approach 1:
The system collects comprehensive fuel pump data but applies partial processing by focusing only on specific metrics that indicate potential issues. Rather than analyzing all possible data points in real-time, the system selectively processes relevant parameters (flow rate, transaction cancellations, help button presses, card read errors, printer errors) against predefined thresholds, reducing processing load while maintaining high issue resolution efficiency.
Data Source
AI summary
Various methods are described for evaluating fuel pump data and determining a fuel pump flow rate. One example method may comprise receiving fuel pump information associated with a fuel pump. The method may further comprise updating previous fuel pump information associated with the fuel pump based on the received fuel pump information. Additionally, the method may comprise detecting an alarm condition associated with the fuel pump based at least in part on the updated fuel pump information. Similar and related methods, apparatuses, and computer program products are also provided.