Location-Based Digital Assistant for Retail Item Discovery
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Solution Overview
Problem
Existing digital assistant apps for shopping are largely passive and do not provide significant utility during the shopping process, failing to leverage available data to enhance user experience in retail or grocery environments.
Innovation Solution
A handheld device with a mobile app that utilizes a positioning subsystem and a server system to provide real-time location-based information, allowing users to interactively locate items of interest within stores by receiving device and item coordinates, determining proximity, and displaying relevant data when within a predetermined threshold.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If digital assistant apps are made passive and simple, then device complexity is reduced, but user experience and utility during shopping deteriorate
Solution Approach 1:
The system enables self-service by automatically tracking user location via positioning subsystem, identifying relevant items based on shopping lists, and pushing notifications without requiring active user search or interaction. The app serves itself by continuously monitoring position coordinates and autonomously determining when to display item information.
Solution Approach 2:
The system implements feedback loops where the positioning subsystem continuously provides location data, the system processes this against stored item coordinates and shopping lists, and dynamically adjusts notifications based on user proximity to target items. This creates adaptive feedback that enhances utility while maintaining simple operation.
2Measurement precision
If real-time location tracking is implemented, then item location accuracy is improved, but device complexity and energy consumption increase
Solution Approach 1:
The patent introduces an intermediary server that handles complex processing of location data, item coordinates, and shopping list matching. The mobile device itself remains relatively simple, delegating computational complexity to the server while maintaining precise location tracking through the positioning subsystem.
Solution Approach 2:
The system implements partial tracking by focusing only on relevant dimensions - tracking position coordinates but only processing information for items on the user's shopping list. This selective approach maintains measurement precision for relevant items while reducing overall system complexity.
3Speed
If continuous positioning monitoring is used, then responsiveness to user location is improved, but energy consumption increases
Solution Approach 1:
The positioning subsystem operates periodically rather than continuously, updating location data at intervals sufficient to track user movement through the store while allowing the device to enter lower-power states between updates. This periodic monitoring maintains responsiveness to location changes while reducing energy consumption.
Solution Approach 2:
The system dynamically adjusts positioning update frequency based on user movement patterns and proximity to target items. When the user is near an item of interest or moving quickly through an aisle, monitoring intensifies; when stationary or in low-activity periods, monitoring reduces, optimizing the balance between responsiveness and energy use.
Data Source
AI summary
A handheld device for use by a user or a consumer, that includes a custom application and is capable of interacting with its physical environment is disclosed. The device utilizes a positioning subsystem located in the device, and a priori or dynamic knowledge locations of stores, items and other geographic position markers. The devices assists the user in identifying and purchasing items of interest, in real time with relevant and timely location based information.