Ambient Content Sampling for Automatic App Discovery
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Solution Overview
Problem
In the crowded gaming app market, users face difficulties in discovering new apps, and existing technologies lack effective methods to seamlessly integrate content-related apps with media consumption, failing to provide artists with control over how their works are presented and experienced.
Innovation Solution
A system where a microphone-equipped device samples ambient content to generate identifying data, which is used to recommend and launch relevant apps, optimizing the user's device to their content preferences, and allowing artists to specify how their work is experienced through app recommendations based on content consumption habits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users manually search and download apps from app stores, then they can discover and install new applications, but the process requires significant user effort and time
Solution Approach 1:
The system performs automatic app discovery and installation without requiring user intervention. The device autonomously samples ambient content, generates identifying data, looks up recommended apps, and installs them automatically, allowing the system to serve itself rather than requiring manual user operation.
Solution Approach 2:
The system pre-loads and prepares app recommendations based on ambient content sampling before the user even searches for apps. By continuously monitoring the environment and pre-identifying relevant applications, the system has app recommendations ready before the user needs them, eliminating the manual search process.
2Adaptability or versatility
If artists have control over app recommendations for their content, then their creative vision is preserved, but the system complexity increases
Solution Approach 1:
The system introduces an intermediary layer between the ambient content and the user device that handles app recommendation logic. This mediator component processes content identification data and matches it with artist-specified app preferences, allowing artist control without requiring direct complex integration into every user device.
3Productivity
If the device automatically recommends and installs apps based on ambient content, then app discovery is enhanced, but the extent of automation increases system complexity
Solution Approach 1:
The system employs a universal content identification mechanism that can recognize multiple types of media (audio, video, text) through a single ambient sampling interface. This multi-functional approach allows the same core infrastructure to handle diverse content types, reducing overall system complexity despite the comprehensive automation provided.
Data Source
AI summary
A gaming event is executed on electronic gaming media. A wager is accepted by a processor and a random selection of both virtual symbols and moves is provided to a player by a display screen on a wagering device. The virtual symbols are randomly arranged on a grid having columns and rows. The player inputs commands to the processor to switch individual pairs of virtual symbols, one pair switched in each available move, until moves are exhausted. A final arrangement of virtual symbols on the grid is evaluated according to paylines and paytables to resolve the wager.