Background Camera Imaging Analysis for In-Store Budget Tracking
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Solution Overview
Problem
Consumers lack access to budgeting and price comparison tools when shopping in physical stores, leading to impulsive purchases and unequal pricing information availability.
Innovation Solution
A first electronic application on a user device extracts item identifiers from imaging data captured by a camera, determines item values, and generates status assessments and actions based on a user's total purchases, using background access to a camera while a second application scans items.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a second electronic application accesses the camera to scan items in a physical store, then the user can identify items and their identifiers, but the first electronic application cannot simultaneously access the same camera data to provide budgeting and price comparison analysis
Solution Approach 1:
The system uses an intermediary mechanism where the first electronic application detects and accesses imaging data that has been captured by the camera through the second application. This intermediary data access layer allows both applications to utilize the same camera resource without direct conflict, enabling the first application to analyze imaging data for budgeting purposes while the second application performs item scanning.
Solution Approach 2:
The system performs preliminary action by capturing and storing imaging data before it is needed for analysis. The camera captures imaging data of items, and this data is made available to the first electronic application in advance, allowing the application to perform budgeting analysis and price comparison without interfering with the ongoing item scanning process.
2Loss of information
If budgeting and price comparison tools are available online, then users can make informed purchasing decisions, but these tools are not accessible when shopping in physical stores
Solution Approach 1:
The first electronic application performs multiple functions including budget tracking, price comparison, and purchasing analysis all within a single application. This multi-functional approach consolidates various financial tools that were previously only available online into one application that works seamlessly in physical store environments, maintaining ease of operation while providing comprehensive pricing information.
Solution Approach 2:
The system implements feedback by continuously monitoring the user's budget status and providing real-time information about whether adding an item would exceed their budget. This feedback mechanism allows users to make informed purchasing decisions at the point of sale in physical stores, similar to having online tools available.
3Productivity
If physical stores structure venues to incite impulsive behaviors, then stores increase sales, but consumers make unplanned purchases without budget consideration
Solution Approach 1:
The system applies preliminary anti-action by proactively preventing impulsive purchases before they occur. The first electronic application detects when a scanned item would cause the user to exceed their budget and provides warning information in advance, allowing the user to make a conscious decision about whether to proceed with the purchase, thereby counteracting the store's impulse-inducing environment.
4Productivity
If customers manually scan and check-out their own purchases, then stores reduce operational costs, but customers lack real-time budget monitoring
Solution Approach 1:
The system enables self-service by allowing customers to scan their own items using the camera and automatically track their purchases against their budget. The first electronic application monitors the scanned items, calculates totals, and provides budget status updates without requiring store staff intervention, thus maintaining store operational efficiency while giving customers real-time budget monitoring capability.
Data Source
AI summary
A method for analyzing imaging obtained from background access to a camera may include detecting, via a first electronic application (the “FEA”) operating on a device, that a second electronic application (the “SEA”) operating on the device, separate from the FEA, is accessing the camera of the device to observe an item identifier (the “II”) of a physical item (the “PI”) to be added to a collection of PIs; extracting, via the FEA, the II from imaging data captured by the camera; determining, via the FEA, a value of the PI based on the extracted II; determining, via the FEA, a total value of the collection based on the value; generating, via the FEA, at least one status assessment of a user associated with the device based on the total value; and executing, via the FEA, at least one action based on the at least one status assessment.