Decentralized Contact Tracing via BLE Device Segmentation
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Solution Overview
Problem
Current contact tracing methods are inefficient and invasive, particularly in large populations, due to their reliance on centralized data storage and lack of user control, which raises privacy concerns and hampers effective disease containment.
Innovation Solution
A decentralized system utilizing portable BLE devices and mobile devices to collect and store semi-anonymous interaction data, with a server-based system for mapping device identifiers to user identifiers, allowing for controlled data access and recursive contact tracing while maintaining user privacy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If centralized data storage is used for contact tracing, then data accessibility and tracing efficiency are improved, but user privacy control and trust deteriorate
Solution Approach 1:
The system segments data storage across multiple devices including portable devices, mobile devices, and servers. Contact data is stored on portable devices, mobile device adjacency data is stored on mobile devices, and mappings between device identifiers and user identifiers are stored on servers. This segmentation allows efficient tracing while maintaining user control over their data.
Solution Approach 2:
The system introduces multiple intermediary layers between data collection and analysis. Portable devices collect contact data, mobile devices store adjacency data, and servers store mappings. This intermediary structure enables efficient data access for tracing while preventing direct centralized collection of all user data, thus protecting privacy.
2Measurement precision
If detailed user information is collected for contact tracing, then tracing accuracy is improved, but user privacy and data security deteriorate
Solution Approach 1:
The system extracts and stores only the necessary data elements for contact tracing. Portable devices store only device identifiers and timestamps of contacts, mobile devices store only adjacency data with minimal information, and servers store only the mappings between device identifiers and user identifiers. This extraction approach maintains tracing accuracy while minimizing data security risks.
Solution Approach 2:
Different types of data are stored at different locations with different levels of detail. Portable devices have local contact data, mobile devices have local adjacency data, and servers have centralized mappings. Each location stores only the quality and type of data needed for its specific function, optimizing both accuracy and security.
3Ease of operation
If manual contact tracing methods are used, then user control over data is maintained, but time consumption and logistical difficulty increase
Solution Approach 1:
The system enables devices to automatically collect, store, and transmit contact data without manual user intervention. Portable devices automatically detect and record contacts, mobile devices automatically store adjacency data, and the system automatically processes tracing queries. This self-service approach maintains user control over data while dramatically reducing time consumption.
Solution Approach 2:
The system continuously collects and stores contact data in the background without interrupting user activities. Portable devices continuously monitor for contacts, mobile devices continuously update adjacency data, and the system continuously maintains mappings. This continuous operation enables rapid tracing responses while requiring minimal user involvement.
Data Source
AI summary
A embodiment may involve receiving a contact tracing request for a first user identifier that corresponds to a first portable device identifier of a first portable device. The second example embodiment may also involve requesting and receiving, from a first computing device associated with the first user identifier, device adjacency data, wherein the device adjacency data contains a plurality of contact entries, wherein one of the contact entries identifies a second portable device identifier of a second portable device that was wirelessly detected by the first portable device and a timestamp of when the wireless detection of the second portable device occurred. The second example embodiment may involve determining, from the mappings, a second user identifier that corresponds to the second portable device identifier. The second example embodiment may further involve transmitting, to a second computing device associated with the second user identifier, a contact tracing notification.