Privacy-Preserving User Engagement via Local Sensor Data Processing
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Solution Overview
Problem
Existing digital signal monitoring techniques, such as the use of cookies, invade user privacy by allowing unaffiliated parties to collect personal information from users' online activities.
Innovation Solution
A computer-implemented method and system that uses physical signals from sensors associated with items to determine user-item associations and item interest levels, allowing for privacy-conscious data collection and communication without relying on cookies or digital signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If cookies are used to monitor digital signals and collect user information, then user engagement and personalized advertising can be improved, but user privacy is compromised as unaffiliated parties can access personal information
Solution Approach 1:
The patent introduces an intermediary system that sits between the user device and third-party websites. This intermediary captures sensor data locally on the user device, processes it to determine user-item associations and interest levels, and then shares only aggregated insights with affiliated parties. The intermediary prevents direct access to personal information by unaffiliated third parties while still enabling personalized advertising and user engagement through controlled data sharing mechanisms.
2Measurement precision
If third-party cookies are deployed to capture user information across multiple websites, then advertising personalization can be enhanced, but data security is weakened as information is exposed to multiple unaffiliated parties
Solution Approach 1:
The patent segments the data collection and processing functions across multiple components: sensor data is collected locally on the user device, processed through local algorithms to determine user-item associations, and then shared in aggregated form with affiliated parties. This segmentation ensures that no single third party receives complete personal information, while still enabling personalized advertising through distributed processing. The segmentation architecture maintains data security by limiting access to only necessary aggregated insights.
3Loss of information
If digital signal monitoring is implemented to track user online activity, then user insights can be gathered for targeted advertising, but user privacy control is reduced as users cannot prevent information collection
Solution Approach 1:
The patent implements self-service mechanisms where the user device itself performs the data collection and processing functions. The device captures sensor data, determines user-item associations locally, and maintains control over what information is shared with affiliated parties. This self-service approach gives users implicit control through device-level processing while still enabling comprehensive user insight gathering for targeted advertising. Users can manage their privacy by controlling which affiliated parties receive aggregated insights.
Data Source
AI summary
The present disclosure is directed to servicing audiences based on object preferences displayed by the audience. The method includes receiving, by a first party computing system, a user communication from a user device associated with a user. The user communication includes a sensor identifier and a user identifier. The sensor identifier corresponds to a physical device associated with at least one item. The method include determining a user-item association based, at least in part, on the sensor identifier and the user identifier. The method includes determining an item interest level for the at least one item based, at least in part, on the user-item association. And, the method includes initiating an action based, at least in part, on the item interest level.