Proximity-Based Output Ranking for Low-Power Media Casting
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Solution Overview
Problem
Existing computing devices struggle to efficiently present a list of available output devices for media content playback, often leading to unnecessary power consumption and incorrect user interactions due to unordered or improperly ranked lists.
Innovation Solution
Implementing proximity-based ranking of available output devices, where wearable computing devices determine and prioritize output devices based on their proximity to the controlling device, and only perform proximity checks for applications likely to cast content, conserving power and reducing resource consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If proximity determination is performed for all available outputs, then the completeness of output selection is improved, but power consumption increases
Solution Approach 1:
The system performs proximity determination selectively rather than universally - it determines the type of source application first, and only performs proximity determination for outputs when the application type indicates casting is likely. This partial action approach maintains reliability for relevant cases while reducing unnecessary power consumption for irrelevant cases.
Solution Approach 2:
The system performs preliminary classification of the source application type before performing proximity determination. By assessing the application type first (e.g., identifying if it's a media player or casting-capable application), the system prepares the conditions for selective proximity checking, avoiding unnecessary power consumption upfront.
2Measurement precision
If proximity determination is performed for all available outputs, then the accuracy of output ranking is improved, but computing resource consumption increases
Solution Approach 1:
The system applies partial action by performing proximity determination only for a subset of available outputs - specifically those associated with applications of types that are likely to cast content. This maintains accurate ranking for relevant outputs while reducing the computational burden of processing all outputs.
Solution Approach 2:
The system applies different processing quality to different outputs based on their association with application types. Outputs associated with casting-capable applications receive full proximity determination (high quality processing), while outputs associated with non-casting applications receive reduced or no proximity determination (lower quality processing), optimizing resource allocation.
3Device complexity
If the list of available outputs is presented in unordered or non-proximity-based order, then the simplicity of the interface is improved, but user interaction efficiency deteriorates
Solution Approach 1:
The system performs preliminary sorting of the output list based on proximity rankings before presenting it to the user. By pre-organizing the list in order of proximity (with the closest output first), the interface maintains simplicity while significantly improving user interaction efficiency, as users can quickly identify and select the most relevant output without scrolling or searching.
Data Source
AI summary
In general, techniques are described for performing proximity-based output selection. A computing device comprising one or more network interfaces and processing circuitry may be configured to perform the techniques. The one or more network interfaces may communicate with one or more available outputs for playing content. The processing circuitry may determine a proximity to the computing device for each of the one or more available outputs, and determine, based on the proximity determined for each of the one or more available outputs relative to every other one of the one or more available outputs, a ranked list of available outputs. The processing circuitry may next interface, with a display, a graphical user interface that includes at least a portion of the ranked list of available outputs.