Context-Aware Information Exchange for AR Devices
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Solution Overview
Problem
Sharing information between computing devices, such as smartphones and augmented reality devices, is problematic due to challenges in determining authorized contexts for information exchange and ensuring the appropriate level of sensitivity, especially in dynamic environments.
Innovation Solution
A system that uses contextual information, including visual data and sensor inputs, to determine authorized contexts for information sharing between devices, establishes a mutually agreeable level of sensitivity, and employs services like facial recognition and location recognition to facilitate secure and relevant information exchange, which is adjusted or terminated based on changes in the context.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If information sharing between devices is enabled without context awareness, then information exchange speed is improved, but information security and relevance deteriorate
Solution Approach 1:
The system performs preliminary context detection and authorization assessment before enabling information sharing. By evaluating contextual factors (location, device type, user identity, environmental conditions) in advance, the system determines whether information exchange should be permitted, thus ensuring security and relevance before data transfer occurs.
Solution Approach 2:
The system introduces context awareness as an intermediary layer between information sources and receivers. This intermediary evaluates contextual conditions and mediates the information exchange process, allowing selective data sharing based on context while maintaining security protocols.
2Reliability
If context detection mechanisms are added to ensure authorized information sharing, then information security is improved, but device complexity increases
Solution Approach 1:
The context detection module is designed as a multi-functional component that simultaneously performs various tasks: detecting contextual factors (location, device type, user identity), assessing authorization conditions, and controlling information flow. This universal approach reduces overall system complexity by consolidating multiple functions into a single integrated mechanism.
Solution Approach 2:
The system employs self-service mechanisms where devices automatically detect their own contextual information and autonomously assess authorization conditions without requiring manual intervention or complex external authentication systems, thereby simplifying the overall architecture.
3Measurement precision
If continuous context monitoring is implemented, then information sharing accuracy is improved, but energy consumption increases
Solution Approach 1:
Instead of continuous monitoring, the system implements periodic context detection that activates based on specific triggers such as device connection events, location changes, or authorization requests. This periodic approach maintains accurate context awareness for information sharing decisions while significantly reducing energy consumption compared to continuous monitoring.
Solution Approach 2:
The system uses feedback mechanisms where context information is updated and re-evaluated only when changes occur or at scheduled intervals. The feedback loop allows the system to maintain accurate context for authorization decisions while minimizing unnecessary processing and energy consumption during stable conditions.
Data Source
AI summary
Information sharing is initiated between devices based on identification, by one or more of the devices, of a context in which the information is to be shared. Services to provide the shared information are identified based on a mutually agreed level of sensitivity for the information sharing. Information is shared between the devices via the services. Use of the services to share information is stopped in response to a change in context identified by one or more of the devices.