Automatic Product Mapping via Crowd-Sourced Sensor Data
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Solution Overview
Problem
Consumers often struggle to find products in physical stores due to the lack of efficient product mapping, leading to missed purchases despite products being available, as existing methods require manual creation and frequent updates of product maps.
Innovation Solution
An automatic product mapping system that utilizes crowd-sourced data from electronic devices to determine product locations within physical stores, correlating sensor data such as location traces, buying behavior, and search behavior to generate dynamic product maps without manual input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual creation and frequent updates of product maps are performed, then product location accuracy is improved, but labor burden and time consumption increase
Solution Approach 1:
The system enables automatic product mapping by leveraging crowd-sourced data from mobile devices naturally carried by consumers. The system processes location traces, buying behavior, and search behavior data to automatically determine product locations without requiring manual intervention for map creation or updates, thus resolving the contradiction between accuracy and time investment
Solution Approach 2:
The system continuously collects crowd-sourced data from multiple consumers and uses this feedback to automatically update and refine product location information. This creates a self-updating system where product maps are dynamically maintained based on real-world consumer behavior patterns, eliminating the need for manual updates while maintaining high accuracy
2Loss of information
If manual product mapping is performed, then product location information is obtained, but the system complexity and operational burden increase
Solution Approach 1:
The system automatically generates and maintains product maps by processing crowd-sourced data from mobile devices. The complexity of data collection, processing, and map generation is handled automatically by the system without requiring manual operational intervention, thus obtaining comprehensive product location information while minimizing operational burden
Solution Approach 2:
The system uses mobile devices carried by consumers as intermediaries to collect location and behavior data. These devices naturally track consumer movements and interactions in the store, converting complex data collection requirements into passive data gathering through the intermediary mobile devices, thereby reducing system operational complexity
3Measurement precision
If crowd-sourced data from multiple devices is collected and correlated, then automatic product mapping accuracy is improved, but data processing complexity increases
Solution Approach 1:
The system merges data from multiple crowd-sourced mobile devices to determine product locations. By combining location traces, buying behavior data, and search behavior data from multiple consumers, the system achieves high accuracy in product location determination while the centralized processing handles the complexity of data integration
Solution Approach 2:
The system processes multiple types of data (location traces, buying behavior, search behavior) from mobile devices using a unified correlation algorithm. This multi-functional approach handles diverse data types through a single processing framework, improving accuracy while managing data processing complexity through standardized procedures
Data Source
AI summary
A method comprising receiving different types of crowd-sourced information, the different types of crowd-sourced information relating to a physical store that a plurality of electronic devices have visited. The method further comprises determining a plurality of products available in the physical store based on the different types of crowd-sourced information, and correlating the different types of crowd-sourced information to determine at least one product location of at least one product of the plurality of products available. Each product location of each product identifies a location of the product within the physical store.