Wearable Sleep Detection for Media Playback Control
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Solution Overview
Problem
Over-the-top (OTT) media platforms continue to stream media content automatically, even if the viewer has fallen asleep, leading to missed content and difficulty in resuming viewing at the correct point.
Innovation Solution
A system and method that respond to a sleep-state event by identifying the type of media content being consumed and generating an appropriate action, such as creating a bookmark or disabling automatic playback, to allow users to easily resume watching at the correct point.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If the OTT platform continues to stream media content automatically without detecting user sleep state, then the automation extent is improved, but the loss of information increases as users miss substantial parts of the series
Solution Approach 1:
The system implements feedback by detecting user sleep state through wearable devices and using this information to adjust the automatic streaming behavior. The platform receives sleep state data from the wearable device and responds by modifying the playback behavior, such as pausing or stopping the stream when the user is detected to be asleep, thereby preventing information loss while maintaining automation.
Solution Approach 2:
The system performs preliminary action by proactively detecting the user's sleep state before significant content is missed. By continuously monitoring wearables for sleep state events, the system can take preventive measures (such as pausing playback) before the user misses important parts of the content, thus resolving the contradiction between automation and information retention.
2Loss of information
If the OTT platform stops streaming after extended period without input, then the loss of information is reduced, but the productivity decreases as users must manually establish resume points
Solution Approach 1:
The system uses feedback from wearable devices to automatically determine when to pause or stop streaming, eliminating the need for arbitrary timeout-based stopping. This feedback mechanism allows the system to accurately identify when the user has fallen asleep and take appropriate action, preventing both excessive content loss and unnecessary manual intervention.
Solution Approach 2:
The system performs self-service by automatically tracking and recording the resume point based on sleep state detection, without requiring user input or manual intervention. The platform autonomously manages the playback state and stores the appropriate resume point, making the system self-sufficient in managing the viewing experience.
3Measurement precision
If the system monitors wearables continuously to detect sleep state, then the measurement precision is improved, but the use of energy increases
Solution Approach 1:
The system employs periodic action by monitoring the wearable device at regular intervals rather than continuously. The platform checks for sleep state events at predetermined time intervals, maintaining adequate measurement precision for detecting sleep states while significantly reducing the energy consumption compared to continuous monitoring.
Data Source
AI summary
Systems and methods are provided for responding to a sleep-state event. One example method includes receiving and generating, at a computing device, media content for output and receiving a sleep-state event. A type of the content being generated for output is identified and, based on the type of content, an action to perform in response to receiving the sleep-state event is identified. The action to perform is generated.