AI Gaming Assistant Using Telemetry for Real-Time Player Guidance
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Solution Overview
Problem
Users often face challenges in accessing timely and personalized assistance during gaming sessions, as conventional information sources are not always available or tailored to their specific skill level, gaming style, and personality.
Innovation Solution
An information handling system equipped with artificial intelligence (AI) analyzes telemetry data, including gaming and wellness metrics, to provide real-time assistance through various interfaces, such as in-game displays, mobile apps, or haptic feedback, using a machine learning model to adapt to the user's performance and preferences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional information sources (online videos, strategy guides, forums) are used for gaming assistance, then gamers can access gaming information, but the information is not timely, personalized, or accessible during active gaming sessions
Solution Approach 1:
The system performs preliminary actions by continuously monitoring gaming telemetry data and sensor inputs before the user explicitly requests assistance. The AI engine analyzes gameplay patterns, skill levels, and mood indicators in advance to predict when assistance is needed, enabling proactive intervention rather than reactive response.
Solution Approach 2:
The system enables self-service by automatically detecting when a user needs assistance based on their gaming behavior patterns and mood state. The AI engine monitors telemetry data, identifies struggling moments, and initiates appropriate assistance without requiring explicit user requests, allowing the system to serve itself in detecting and responding to user needs.
2Adaptability or versatility
If general gaming information sources are used, then gamers can find gaming tips, but the information is not tailored to individual skill level, gaming style, or mood
Solution Approach 1:
The system applies local quality by tailoring assistance content to the specific local context of each user's gaming session. The AI engine analyzes individual gaming characteristics, skill level, and mood state to customize assistance strategies for each user, ensuring that the assistance is relevant and appropriate for their specific situation rather than providing generic information.
Solution Approach 2:
The system utilizes parameter changes by dynamically adjusting assistance parameters based on real-time monitoring of user mood, skill level, and gaming context. The AI engine modifies assistance intensity, type, and timing based on changing parameters such as user excitement levels, difficulty of current gameplay, and historical performance data, enabling adaptive personalization.
3Productivity
If multiple sensors and AI processing are integrated into the hub device, then real-time personalized assistance can be provided, but the device complexity increases
Solution Approach 1:
The hub device achieves universality by integrating multiple functions including AI processing, sensor data collection, gaming application execution, and assistance delivery into a single multi-functional platform. This consolidation allows the system to provide real-time personalized assistance without requiring separate dedicated devices for each function, managing complexity through functional integration.
Data Source
AI summary
Systems and methods for providing assistance with a user's gaming performance are disclosed. Telemetry data associated with a user is received, e.g., by an information handling system or hub device, during a gaming session for a gaming application. A gaming performance of the user is monitored during the gaming session, based, at least in part, on the telemetry data. Based on the monitoring, it may be determined that the user needs assistance with at least one portion of the gaming application. Based on the determination, a gaming assistance session is initiated to provide the assistance via at least one interface of a device associated with the user.