Media Selection Based on Anticipated Activity
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Solution Overview
Problem
Current computing devices require users to manually select media based on their activities, as media suggestions are typically tied to user profiles rather than current or anticipated activities, leading to an inefficient media selection process.
Innovation Solution
A computing device system that determines an anticipated activity by analyzing user actions and selects appropriate media to play, using a processor and memory to execute code that identifies current actions, determines future activities, and plays media accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If media suggestions are tied to user profiles, then media recommendations can be personalized, but media selection does not reflect current or future activities requiring manual user input
Solution Approach 1:
The system performs preliminary actions by detecting current user actions and anticipating future activities before the user needs media. The media player proactively selects and prepares media based on predicted user needs, eliminating the need for manual selection at the moment of use.
Solution Approach 2:
The media selection system serves itself by automatically detecting user actions, predicting activities, and selecting appropriate media without requiring user intervention. The system uses user profile data and action detection to autonomously make media selection decisions.
2Productivity
If the system automatically detects user actions and anticipates activities, then media selection efficiency improves, but system complexity increases
Solution Approach 1:
The media player is enhanced with multi-functionality, combining media playback with action detection and activity anticipation capabilities. This universal system performs multiple functions (media selection, action detection, activity prediction) within a single device, managing complexity through integration.
Solution Approach 2:
The system introduces an intermediary layer between user actions and media selection that analyzes actions and predicts activities. This intermediary processing layer translates raw user actions into meaningful activity predictions that guide media selection, managing the complexity of the overall system.
Data Source
AI summary
Methods, apparatus, and computer program products that can play a media selection based on an anticipated activity are disclosed herein. One method includes determining, by a processor, an anticipated activity for a user based on one or more actions being currently performed by the user, determining a media selection for the user based on the determined anticipated activity, and playing the determined media selection. Apparatus and computer program products that include hardware and/or software that can perform the methods for playing a media selection based on an anticipated activity are also disclosed herein.