Pre-caching Streaming Content via Sensor-Based Prediction
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Solution Overview
Problem
Delays occur when switching between streaming content on information handling devices due to the time required to load new content, which can disrupt the viewing experience.
Innovation Solution
An apparatus and method for pre-caching streaming content, using a processor and memory to detect input from sensors such as accelerometers and cameras to predict changes in content, and proactively cache a predetermined period of streaming content based on viewing history and patterns, allowing for smoother transitions between streams.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If content is loaded on-demand when switching between streaming content, then network bandwidth is conserved, but switching delay increases
Solution Approach 1:
The system performs preliminary actions by detecting user intent to switch content (via sensor inputs like remote control detection or viewing pattern analysis) and proactively pre-loads the next content into cache memory before the actual switch occurs. This anticipatory caching eliminates switching delays while bandwidth is still efficiently utilized by only pre-loading when switching is predicted.
Solution Approach 2:
The system implements feedback loops by continuously monitoring sensor inputs (remote control detection, device orientation, viewing history) and adjusting the pre-caching strategy in real-time. When sensors indicate the user is about to switch content, the system activates pre-loading; when no switch is detected, pre-loading is suspended, optimizing the balance between switching speed and bandwidth usage.
2Productivity
If content is pre-loaded into cache, then switching speed improves, but cache memory fills faster
Solution Approach 1:
Instead of fully pre-loading entire content items, the system applies partial action by pre-loading only the necessary portions of content (e.g., next few minutes of video) into cache based on predicted switching patterns. This selective pre-caching provides sufficient buffering for smooth switching while consuming minimal cache memory resources.
Solution Approach 2:
The system performs preliminary caching of content segments before they are needed, using prediction algorithms based on viewing history and sensor data to determine which content segments to pre-load. This allows the cache to be optimally populated with only the most likely next content, improving switching speed without unnecessarily filling cache memory.
3Measurement precision
If sensor detection is used to predict content changes, then pre-caching accuracy improves, but device complexity increases
Solution Approach 1:
The system leverages existing sensors already present in modern devices (accelerometers, gyroscopes, remote control receivers) that are designed to detect user interactions anyway. By repurposing these existing sensors for content switching prediction, the system improves prediction accuracy without adding significant hardware complexity, as the sensors are already part of the device's standard configuration.
Data Source
AI summary
Apparatuses, methods, and program products are disclosed for pre-caching streaming content. One apparatus includes a processor, and a memory that stores code executable by the processor. The code is executable by the processor to determine to perform pre-caching of streaming content. The code is also executable by the processor to determine a streaming content to pre-cache. The code is executable by the processor to pre-cache the streaming content.