Gaze Context Notification Delivery on Heterogeneous IHS Platforms
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Solution Overview
Problem
The transition from x86 to ARM-based processors in Information Handling Systems (IHS) has created challenges in managing, customizing, and optimizing notifications, as existing systems lack efficient methods to determine user context and deliver notifications effectively across heterogeneous computing platforms.
Innovation Solution
The implementation of a heterogeneous computing platform in IHS that detects user gaze context to determine when to deliver notifications or queue them for later delivery, utilizing resources such as System-On-Chip (SoC), Field-Programmable Gate Array (FPGA), or Application-Specific Integrated Circuit (ASIC), and an orchestrator like the Embedded Controller (EC) or Baseboard Management Controller (BMC) to manage notification delivery based on user focus and historical gaze data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If notifications are delivered immediately to users, then information delivery speed is improved, but user distraction increases during focused activities
Solution Approach 1:
The system performs preliminary analysis of user gaze context before delivering notifications. The eye-tracking system continuously monitors user focus in advance, and notifications are queued and evaluated based on predicted user attention states, allowing the system to prepare notification delivery decisions before actual delivery occurs.
Solution Approach 2:
The system implements feedback loops where notification delivery decisions are continuously adjusted based on real-time gaze data. The eye-tracking system provides feedback about user attention state to the notification manager, which then modifies delivery timing dynamically. This closed-loop control ensures notifications are delivered when users are actually paying attention, reducing distractions during focused activities.
2Reliability
If gaze tracking is continuously monitored to determine notification timing, then notification relevance is improved, but system complexity increases
Solution Approach 1:
The system segments the complex gaze analysis task into distinct functional modules: eye-tracking hardware layer, gaze data processing layer, attention state classification layer, and notification decision layer. Each module handles a specific aspect of the problem, making the overall system more manageable and maintainable while achieving high notification delivery accuracy.
Solution Approach 2:
The patent introduces an orchestrator component that acts as an intermediary between the heterogeneous computing platform resources and the notification system. This orchestrator manages the complex interactions between eye-tracking data, user context, and notification delivery decisions, simplifying the overall system architecture while maintaining high reliability in notification timing.
3Power
If heterogeneous computing resources are utilized for gaze context analysis, then processing capability is improved, but device complexity increases
Solution Approach 1:
The system implements a universal orchestrator framework that can allocate and manage multiple types of computing resources (CPU, GPU, NPU, FPGA) for gaze context analysis. This multi-functional architecture allows the same system to handle different workloads using appropriate hardware accelerators, improving processing capability while providing a unified interface that masks the underlying complexity.
Solution Approach 2:
The orchestrator serves as an intermediary layer between the heterogeneous computing resources and the application layer. It abstracts the complexity of resource management by providing a unified interface for gaze analysis tasks, allowing applications to request processing without needing to know which specific hardware resource will handle the computation.
4Productivity
If notifications are queued for deferred delivery based on gaze context, then user productivity is improved, but notification delivery time increases
Solution Approach 1:
The system implements periodic re-evaluation of queued notifications based on user gaze patterns. Instead of holding notifications indefinitely, the system checks at regular intervals whether delivery conditions are met, balancing the need to maintain user productivity with the requirement to deliver time-sensitive information promptly when attention is detected.
Data Source
AI summary
Systems and methods are provided for utilizing a heterogeneous computing platform of an IHS (Information Handling System) to manage notifications that are provided to a user of the IHS. Notification that are generated for delivery to the user of the IHS are detected. Using resources of the heterogeneous computing platform, a current gaze context of the user is determined, where the gaze context includes the focus of the user's gaze. Based on the gaze context, the notification is delivered to the user or the notification is queued for deferred delivery to the user, where a notification may be delivered if relevant to the user interface that is the focus of the user's gaze and may be otherwise queued, thus refraining from distracting the user.