Automated User Detection via Proximity Identification
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing recommendation systems face challenges in accurately attributing customer data to the correct user account, especially in scenarios where multiple users share a common device or system, leading to difficulties in providing effective item recommendations.
Innovation Solution
Implementing device-enabled identification for automated user detection, which allows content consumption devices to automatically select the correct user account by detecting identifying devices within consumption proximity, thereby eliminating the need for manual account switching.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual account switching is used in shared devices, then users can access their personal data, but accurate attribution of customer data to the correct user account deteriorates
Solution Approach 1:
The system automatically detects user presence through device sensors (camera, microphone, sensors) and autonomously switches between user accounts without requiring manual intervention. The device serves itself by identifying users and attributing their actions to the correct accounts, eliminating the need for users to manually switch accounts while maintaining accurate data attribution.
Solution Approach 2:
The patent replaces the mechanical manual account switching process with an automated detection system using cameras, microphones, and sensors to identify users. This substitution of mechanical user action with automated technological detection resolves the contradiction by eliminating manual intervention while preserving accurate user identification.
2Measurement precision
If automated user detection is implemented, then accurate attribution of user data is improved, but device complexity increases
Solution Approach 1:
The patent leverages existing multi-functional device components (camera, microphone, sensors) already present for other purposes and repurposes them for user detection. By making existing components serve multiple functions, the system achieves accurate user attribution without adding significant complexity, as the same hardware is used for both original purposes and user identification.
Solution Approach 2:
The system introduces software algorithms and processing logic as intermediaries that connect existing hardware components to user identification functionality. These intermediary software layers coordinate the various sensors and cameras to detect and identify users, managing the complexity through modular software architecture rather than requiring complex hardware modifications.
3Adaptability or versatility
If multiple users share a common device, then device versatility is improved, but the ability to provide personalized recommendations deteriorates
Solution Approach 1:
The system segments the shared device experience into distinct user-specific sessions by automatically detecting which user is present and switching to their personalized account. This segmentation allows the device to maintain separate recommendation profiles, purchase histories, and preferences for each user, enabling personalized recommendations despite multiple users sharing the same physical device.
Data Source
AI summary
A content consumption system or device may implement device-enabled identification for automated user detection. An identifying device may be detected at a content consumption device as within proximity of the content consumption device. An identifying device may be a mobile or wearable computing device, in various embodiments. A user account associated with the identification device may be selected for accessing content at the content consumption device. Access to content may be provided according to the selected user account. In some embodiments, content recommendations or content filtering may be performed based on the automatically determined user account.