Input Device Identification via Signal Confidence Scoring
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Gaming consoles face challenges in distinguishing between approved and unapproved input devices, as unapproved devices like keyboards and mice, connected through intermediate devices, can modify signals to resemble those of approved controllers, potentially providing users with an unfair advantage.
Innovation Solution
A method is implemented in computing devices to identify approved input devices by analyzing input signals from target user-actuatable components, applying rules to generate a confidence score, and comparing it to a threshold score, which involves analyzing signal patterns, latency, and responses to determine if the input components are associated with an approved device.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If intermediate devices modify input signals from unapproved devices to resemble approved controllers, then unapproved devices can provide input to the gaming console, but the console cannot distinguish between approved and unapproved input devices
Solution Approach 1:
The system performs preliminary analysis of input signal characteristics before processing them further. By examining signal patterns, latency, and response characteristics in advance, the console can identify unapproved devices before they provide input, preventing the identification problem from occurring during actual gameplay
Solution Approach 2:
The system uses feedback loops to continuously monitor and analyze input signals. By comparing received signals against known patterns from approved devices and adjusting identification algorithms based on observed characteristics, the system improves its ability to distinguish approved from unapproved devices even when signals are modified
2Measurement precision
If the console analyzes multiple input signal characteristics including latency and signal patterns, then identification accuracy improves, but processing complexity increases
Solution Approach 1:
The identification process is divided into separate modular analysis stages: signal pattern recognition, latency measurement, and response characteristic analysis. Each stage processes specific aspects independently and passes results to the next stage, making the overall complex process more manageable and efficient
Solution Approach 2:
The system applies a tiered analysis approach where basic identification uses a subset of signal characteristics, while more thorough analysis applies additional characteristics only when needed. This partial action approach maintains accuracy while reducing average processing complexity
Data Source
AI summary
Examples are disclosed that relate to computing devices and methods for identifying an approved input device. In one example, a method comprises: receiving a plurality of input signals from a plurality of target user-actuatable input components operated by a user, applying a plurality of rules to the plurality of input signals to generate a confidence score, and comparing the confidence score to a threshold score to determine if the plurality of target user-actuatable input components are associated with an approved input device.