Gaming Accessory Management for Automated Gameplay Action Detection
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Solution Overview
Problem
Efficient management and utilization of multiple gaming accessories is challenging, impacting a gamer's performance, especially in online or competitive games, and this issue extends to other disciplines where accessory management is crucial.
Innovation Solution
The implementation of Accessory Management Software (AMS) that monitors and manages gaming accessories by detecting actions during gameplay, applying tags, and storing memorable moments, leveraging machine learning and artificial intelligence to enhance accuracy in identifying noteworthy events, and allowing for customization and association of actions with input functions across different accessories.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple gaming accessories are used simultaneously, then gaming functionality and performance are improved, but accessory management complexity increases
Solution Approach 1:
The patent introduces an accessory management system that acts as an intermediary between multiple gaming accessories and the gaming device. This system automatically detects, identifies, and manages accessory configurations, reducing the manual management burden on users while enabling the use of multiple accessories simultaneously for enhanced gaming functionality.
Solution Approach 2:
The accessory management system implements self-service capabilities by automatically detecting connected accessories, identifying their types and functions, and configuring them without requiring manual user intervention. The system autonomously manages accessory assignments and optimizations, freeing users from complex management tasks while maintaining versatile gaming capabilities.
2Ease of operation
If accessory management automation is increased, then ease of operation is improved, but system complexity increases
Solution Approach 1:
The system implements self-service by automatically detecting accessories, identifying their functions, and configuring them without user intervention. This automation improves ease of operation while the system handles the complexity internally through intelligent algorithms for accessory recognition and configuration management.
Solution Approach 2:
The accessory management system uses feedback mechanisms to continuously monitor accessory status, performance, and compatibility. Based on this feedback, the system dynamically adjusts configurations and manages accessory assignments, providing automated ease of operation while managing system complexity through adaptive control loops.
3Measurement precision
If action detection accuracy is improved using machine learning, then measurement precision is improved, but computational requirements and processing time increase
Solution Approach 1:
The system performs preliminary actions by pre-processing and analyzing accessory data streams in real-time before full game actions occur. Machine learning models are pre-trained and ready to quickly classify detected actions, reducing processing time during actual gameplay while maintaining high detection accuracy through advance preparation and optimization.
Data Source
AI summary
A system that incorporates the subject disclosure may include, for example, a processor that facilitates a performance of operations. The operations may include obtaining an identification of an action to monitor during a gameplay associated with a game, storing a representation of a sliding window of the gameplay in a first storage medium, monitoring, by the system, for the identification of the action during the gameplay, detecting the identification of the action during the gameplay responsive to the monitoring, and responsive to the detecting, storing the representation of the sliding window of the gameplay in a second storage medium that is different from the first storage medium. Additional embodiments are disclosed.