Anonymizing Interface for Privacy-Safe Wellness Data Analysis
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Solution Overview
Problem
Current monitoring systems face challenges in accessing and analyzing individual data for statistical purposes due to privacy concerns, as sensitive information is protected by laws and regulations, limiting the combination and use of such data for wellness improvement, even when intended to benefit the individual.
Innovation Solution
A monitoring system with an anonymizing interface is developed to combine data-mining and presence technology, making individual observables anonymous based on information protection criteria, allowing for the creation of dynamic observables and system statuses that can be used in management systems without revealing personal information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If individual data is collected and analyzed for statistical purposes, then wellness management and service optimization are improved, but personal privacy and information security are compromised
Solution Approach 1:
The patent introduces an anonymizing interface as an intermediary component between data collection and statistical analysis. This interface transforms individual observables into anonymous ensemble observables by removing personally identifiable information while preserving statistical properties, thereby enabling wellness management analysis without direct exposure of personal data
Solution Approach 2:
The system creates anonymized copies of individual data through the anonymizing interface. These copies contain statistical information sufficient for wellness management purposes while eliminating personal identifiers, allowing analysis to proceed on replicated data rather than original sensitive information
2Reliability
If personal information is protected and kept secret, then individual privacy is maintained, but the ability to combine and analyze data for wellness improvement is limited
Solution Approach 1:
The patent segments information into different levels: individual observables (protected), anonymized ensemble observables (accessible for analysis), and statistical information (fully accessible). The anonymizing interface performs this segmentation by separating personally identifiable information from statistical properties, allowing different portions of data to be accessed according to their sensitivity level
Solution Approach 2:
The system changes the parameters of data representation through anonymization. Individual data points are transformed from identifiable records to anonymous statistical contributions, changing the parameter set from including personal identifiers to only including aggregate statistical properties that preserve analytical value while removing privacy risks
3Productivity
If data mining algorithms are applied to large amounts of data, then statistical analysis capability is improved, but the risk of exposing sensitive information through data combination increases
Solution Approach 1:
The patent applies preliminary anonymization action before data mining algorithms are executed. The anonymizing interface processes individual observables into anonymous ensemble observables in advance, ensuring that when data mining and statistical analysis are performed on the anonymized data, no personally identifiable information can be exposed through combination or correlation analysis
Data Source
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AI summary
An apparatus for providing synchronized navigation may include a processor. The processor may be configured to provide for concurrent display of information related to a space dimension on a background layer and information related to a linear dimension on a foreground layer, wherein the foreground layer is provided as an overlay over at least a portion of the background layer. The processor may be additionally configured to provide for synchronized navigation of the foreground layer and the background layer. Associated methods and computer program products may also be provided.