Wearable Data Provenance Verification for Long-Term Storage
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Solution Overview
Problem
Current wearable computing devices face challenges in securely and efficiently storing and verifying physiological data from multiple sources, including sensors and environmental data, to provide comprehensive health monitoring and long-term medical insights.
Innovation Solution
A method and system where a computing device receives and verifies data items from wearable devices, determining the source and provenance of the data to associate it with a biological entity, and stores this data in a standardized format for long-term storage and retrieval, enabling secure and efficient data management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data from multiple sources including wearable devices is stored without verification, then data quantity and comprehensiveness are improved, but data reliability and security deteriorate
Solution Approach 1:
The system performs preliminary verification actions before storing data items. The computing device determines the source of each data item, verifies provenance information, and confirms association with the biological entity before acceptance into the data log. This preliminary verification prevents unreliable data from being stored while allowing comprehensive data collection from multiple verified sources.
Solution Approach 2:
The computing device acts as an intermediary between multiple data sources (wearable devices, sensors) and the data storage system. It mediates the data flow by verifying provenance and source information, ensuring that only authenticated data items associated with the correct biological entity are stored, thus maintaining data reliability while accepting data from multiple sources.
2Measurement precision
If provenance verification is performed for each data item, then data security and accuracy are improved, but processing time and system complexity increase
Solution Approach 1:
The system performs verification actions selectively rather than exhaustively for all possible attributes. It focuses on verifying provenance and source association as essential partial actions, rather than performing complete comprehensive validation of all data characteristics. This approach achieves sufficient data accuracy while minimizing unnecessary processing time.
3Loss of information
If comprehensive health data is stored long-term, then medical diagnostic value is improved, but data management complexity and storage requirements increase
Solution Approach 1:
The system segments data management into distinct functional components: data reception from multiple sources, provenance verification, source determination, association verification, and storage in structured data logs. This segmentation of the data management process reduces overall complexity by making each component independent and manageable while preserving comprehensive health information for long-term storage and medical diagnostic use.
Data Source
AI summary
Methods and apparatus for storing data about biological entities are provided. A computing device can receive a plurality of data items about a biological entity from a plurality of sources. The computing device can verify each data item of the plurality of data items using the computing device by at least: determining a source of the data item from among the plurality of sources, determining a provenance for the data item associated with the source of the data item, and verifying that the data item is associated with the biological entity based at least on the provenance for the data item associated with the source of the data item. After verifying that a particular data item is associated with the biological entity, the computing device can store the particular data item in a data log associated with the biological entity.