Product Dispenser Mobile Payment Link Without Cloud Connectivity
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Solution Overview
Problem
Fuel dispensers at fueling stations experience meter drift between annual calibrations, leading to inaccuracies in fuel dispensing, which can result in customer or station losses, inventory discrepancies, environmental contamination, and non-compliance with regulations, with existing systems failing to detect these issues in a timely manner.
Innovation Solution
A system and method for real-time determination of meter drift using predictive modeling and physics-based fluid balancing, incorporating sensors and data processing to estimate and quantify losses due to meter drift, utilizing predictive models and error correction techniques to account for discrepancies in fuel storage facilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If annual calibration of flow meter is performed, then measurement precision is maintained, but time between calibrations allows meter drift to occur causing loss of measurement precision
Solution Approach 1:
The system performs preliminary detection of meter drift conditions by continuously monitoring fuel storage facility data and comparing actual fuel levels against predicted levels based on sales and deliveries. This early warning approach allows calibration to be performed just when needed, rather than on a fixed annual schedule, thereby maintaining measurement precision while minimizing unnecessary calibration intervals.
Solution Approach 2:
The system implements continuous feedback monitoring by tracking fuel inventory levels, sales transactions, and delivery records to detect deviations indicating meter drift. When drift is detected, the system generates alerts prompting calibration action. This feedback loop ensures measurement precision is maintained by triggering calibration only when actual drift occurs, optimizing the balance between calibration frequency and measurement accuracy.
2Measurement precision
If frequent monitoring of meter drift is implemented, then measurement precision and compliance are improved, but device complexity and operational costs increase
Solution Approach 1:
The system uses existing infrastructure components (fuel dispensers, point of sale systems, delivery records, and automated tank gauges) to automatically collect and analyze data for meter drift detection. By leveraging these self-existing data sources and processing capabilities, the system achieves frequent monitoring without requiring additional complex hardware or manual intervention, thus improving detection accuracy while minimizing added complexity.
Solution Approach 2:
The monitoring system is designed to serve multiple functions: it tracks fuel inventory levels, monitors sales transactions, records deliveries, detects meter drift, and generates compliance reports. By making the system multi-functional and integrating these capabilities into a unified platform, the patent reduces overall system complexity while enabling comprehensive meter drift monitoring and measurement precision maintenance.
3Object-affected harmful factors
If real-time meter drift detection is implemented, then losses and environmental risks are reduced, but implementation costs and system complexity increase
Solution Approach 1:
The system introduces an intermediary analytical layer that processes data from existing infrastructure components (dispensers, tank gauges, POS systems) to detect meter drift conditions. This intermediary layer translates raw operational data into actionable drift detection without requiring direct modification of existing equipment, thereby reducing environmental risks through real-time detection while minimizing the complexity increase associated with implementation.
4Measurement precision
If predictive modeling is used to detect meter drift, then measurement precision is maintained between calibrations, but computational resources and processing requirements increase
Solution Approach 1:
The system applies predictive modeling selectively rather than continuously processing all possible data. It focuses on key indicators such as fuel level discrepancies, transaction volumes, and delivery records to detect meter drift. By applying computational analysis only when relevant data patterns suggest potential drift conditions, the system maintains measurement precision while minimizing unnecessary computational energy consumption.
Data Source
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AI summary
Various exemplary methods and devices for product dispenser electronic communication with a mobile device are provided. In general, a mobile device can request a secure connection with a product dispenser detected in the proximity of the mobile device. The mobile device can transmit request data to a network cloud server to authorize a mobile payment application executed on the mobile device, and can receive response data from the network cloud server indicating that the payment application has been authorized to process a payment for a product dispensable from the product dispenser. The mobile device and the product dispenser establish a secure connection using a secure key included in the response data, regardless of whether or not the product dispenser has established a connection with a network cloud server.