Trip Content Download Planning for Predicted Viewing Progress
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Solution Overview
Problem
Frequent travelers face limitations in accessing desired content during trips due to geographical restrictions and inconsistent viewing progress, leading to incomplete episode downloads and inefficient manual interaction with program guides.
Innovation Solution
A system that dynamically optimizes content downloads based on consumption patterns and geographic restrictions by predicting consumption progress points and adjusting media assets on a device before a trip, automatically downloading necessary episodes to ensure continuous viewing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the consumer device downloads all episodes of a series, then the user has continuous content availability during the trip, but the processing storage and memory of the consumption device become filled up
Solution Approach 1:
The system performs preliminary actions by downloading content before the trip based on predicted consumption patterns. It calculates the first progression point (where the user is likely to be before departure) and second progression point (where the user will be during the trip), then downloads only the necessary episodes in between, avoiding both over-download and under-download scenarios.
Solution Approach 2:
The system dynamically adjusts the content download strategy based on actual consumption patterns. It monitors the user's viewing progress and updates the progression points accordingly, allowing the download plan to adapt to changing user behavior rather than following a static pre-determined plan.
2Ease of operation
If the user manually downloads episodes before departing, then the user can control content selection, but the process becomes labor-intensive and may result in incomplete episode downloads
Solution Approach 1:
The system enables self-service by automatically monitoring the user's consumption patterns and autonomously determining which episodes to download. The system calculates progression points based on viewing speed and trip duration, then automatically downloads the appropriate content without requiring manual user intervention, thereby eliminating the time and effort spent on manual selection and downloading.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring the user's actual consumption patterns and comparing them with predicted patterns. This feedback loop allows the system to adjust the progression points and download recommendations in real-time, improving the accuracy of content predictions and ensuring the user has the right content available.
3Volume of stationary object
If the system predicts consumption progress points to optimize downloads, then storage efficiency is improved, but the system complexity increases due to tracking and predicting consumption patterns
Solution Approach 1:
The system performs preliminary calculations of consumption patterns and progression points before the trip begins. By estimating the user's viewing speed and calculating where they will be at departure and during the trip, the system can pre-determine the optimal download set, simplifying the actual execution phase while maintaining storage efficiency.
Solution Approach 2:
The system utilizes parameter changes in consumption behavior to optimize downloads. It monitors changes in viewing patterns, episode completion rates, and user preferences, then adjusts the progression point calculations accordingly. This allows the system to adapt to varying user behaviors without requiring complex reconfiguration.
Data Source
AI summary
Systems and methods are described herein for retrieving an information file from a user profile about a scheduled trip, where access to content may be restricted and identifying, based on the consumption pattern, a first progression point before the scheduled start time and a second progression point after the scheduled end time of the scheduled trip. Based on the difference between the first and second progression points, the media guidance application causes to be stored the respective media assets on a consumption device. Then before departing for the scheduled trip, the media guidance application confirms the first progression points against the current progression point and causes to adjust the stored media assets based on a difference between the current progression point and the first progression point.