Smart Home Privacy-Aware Content Selection via Local Data Segmentation
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Solution Overview
Problem
Smart-device environments face challenges in providing personalized content due to limited detailed user information and privacy concerns, which restrict the collection of historical data needed for relevant content delivery.
Innovation Solution
A private network within the smart-device environment allows data communication between devices without leaking outside, enabling devices to capture and use people/object data to select content based on scores assigned by a server, preserving user privacy and enhancing content personalization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If detailed user information is collected to provide personalized content, then content relevance is improved, but user privacy is compromised
Solution Approach 1:
The system segments the content selection process into two parts: the server provides a set of potential content with scores, but the final selection is made locally by the smart device using captured people/object data. This segmentation keeps detailed user data within the private network while still enabling personalized content delivery.
Solution Approach 2:
The smart device acts as an intermediary between the server and the user. It receives potential content from the server, captures local environment data using its camera, and makes the final content selection locally without transmitting detailed user information to the server.
2Loss of information
If historical user data is collected to enhance personalization, then content personalization is improved, but data security is worsened
Solution Approach 1:
The smart device performs self-service by capturing people/object data locally and making content selection decisions autonomously based on this local data and server-provided scores. This eliminates the need to transmit detailed user data to external servers, thereby enhancing data security while maintaining personalization accuracy.
3Loss of information
If user data is transmitted to external servers for content selection, then content personalization is improved, but network security is compromised
Solution Approach 1:
Instead of the conventional approach where user data is transmitted to external servers for analysis, this system inverts the process: the server only sends potential content with scores, while the smart device performs the analysis locally using captured environment data. This keeps detailed user data within the private network.
Solution Approach 2:
The system moves the content selection process from the cloud dimension to the edge dimension (local device). By performing content selection locally on the smart device rather than centrally on external servers, the system enables personalization while enhancing network security.
Data Source
AI summary
In one embodiment, a computing system may operate within a local area network. The computing system may include a network interface configured to receive a set of content items from a content server located remotely from the computing system and the local area network, a storage element for storing the set of content items, and a processor. The processor may be configured to determine first data relating to people, objects, or some combination thereof, select at least one content item from the set of content items based at least in part on the first data relating to people, objects, or some combination thereof without communicating the first data to the content server or any other computing device outside of the local area network, and communicate the selected at least one content item to a user of the computing system.