Camera-Based Fueling Station Checkout for Frictionless Vehicle Commerce
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Solution Overview
Problem
Current fueling station infrastructure lacks automation in transactions between vehicles and commerce, leading to inefficiencies and friction in the user experience, particularly with the transition to electric vehicles and autonomous driving.
Innovation Solution
A camera-based commerce system that utilizes computer vision to monitor and automate transactions at fueling stations and vehicle-related environments, enabling seamless digital payments and unified commerce experiences by tracking users and products through image data, allowing for automatic checkout and payment processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual checkout processes are used at fueling stations, then transaction accuracy can be maintained through human verification, but transaction time and operational complexity increase
Solution Approach 1:
The patent replaces manual mechanical checkout processes with an automated computer vision system using cameras and image processing algorithms. The system automatically detects products, tracks them to customers, and processes payments without human intervention, thereby reducing transaction time while maintaining accuracy through automated image analysis.
Solution Approach 2:
The system enables self-service checkout where customers are automatically identified and charged for products they take based on computer vision tracking. The automated system monitors product movement, identifies when items leave shelves, and charges associated customers without requiring manual scanning or checkout procedures.
2Productivity
If computer vision systems are deployed for automated commerce monitoring, then productivity and automation are improved, but device complexity and implementation difficulty increase
Solution Approach 1:
The patent implements a multi-functional computer vision system that performs product detection, customer tracking, payment processing, and inventory management through a single integrated platform. The camera network serves multiple purposes: monitoring product locations, identifying customers, tracking item movement, and triggering automated charges, thereby managing complexity through consolidation.
Solution Approach 2:
The system introduces an intermediary processing layer that bridges physical product movement and digital transaction processing. Image processing algorithms act as intermediaries, translating visual data from cameras into actionable commerce information, which then triggers automated charging decisions, thereby managing system complexity through modular information transformation.
3Ease of operation
If automated image processing is used to track products and users, then ease of operation is improved, but measurement precision and detection difficulty increase
Solution Approach 1:
The system performs preliminary actions by pre-establishing customer associations with payment methods and pre-mapping product locations and identifiers. When customers enter the store, their accounts are already linked to their profiles, and product codes are pre-configured in the system, enabling automatic recognition and charging without real-time manual verification.
Solution Approach 2:
The system implements feedback loops where image processing continuously monitors product locations and customer movements, verifies detection accuracy against known product databases, and adjusts tracking parameters in real-time. This feedback mechanism ensures high measurement precision by constantly validating detected objects against expected patterns and correcting errors.
Data Source
AI summary
A system and method for vehicle facilitated commerce comprising: collecting a payment mechanism associated with a vehicle station at a vehicle service site; collecting image data in a defined region containing the vehicle station and a defined commerce region; initializing monitoring of at least one detected user associated with the vehicle station; monitoring commerce activity of the user, which comprises of: through CV processing of image data, detecting at least one commerce activity event involving the user and updating a checkout list associated with the user based on the commerce activity event; and executing a transaction with the payment mechanism for the checkout list.