Context-Aware Event Detection for Real-Time Coaching Notifications
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Solution Overview
Problem
Conventional event notification systems fail to account for the context of the recipient or circumstances when delivering notifications, often providing isolated prompts without considering the state of the user or the context of the event.
Innovation Solution
A real-time contextual event notification system that processes event messages to determine context and deliver targeted notifications based on user interactions and circumstances, utilizing a cloud-based architecture with components like recorder integration servers, managed streaming components, and client management services to provide context-aware alerts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If conventional event notification systems use a simple 'if this, then that' paradigm, then the system complexity is low and ease of operation is high, but the notification relevance and context-awareness deteriorate
Solution Approach 1:
The system segments the notification process into distinct functional components: event detection module that identifies application events, context determination module that analyzes user state and event circumstances, and notification delivery module that delivers personalized notifications. This segmentation allows each component to specialize in one aspect, maintaining manageable complexity while achieving comprehensive context-awareness through the coordinated interaction of specialized modules
Solution Approach 2:
The patent introduces a context determination module as an intermediary between event detection and notification delivery. This intermediary module processes both the application event data and user state information, synthesizing them into contextual understanding that informs notification personalization. The intermediary absorbs the complexity of context analysis, shielding the simpler event detection and notification delivery components while enabling rich contextual awareness
2Loss of information
If the system processes multiple data streams to determine context, then the notification relevance improves, but the processing time and loss of time increase
Solution Approach 1:
The system performs preliminary actions by continuously maintaining an updated representation of user state in the background, independent of specific events. User interactions, application states, and contextual information are pre-processed and stored in a readily accessible format. When an application event occurs, the pre-prepared user state information can be immediately retrieved and combined with the event data, eliminating the need for time-consuming analysis at the moment of notification trigger
Solution Approach 2:
The context determination operates continuously rather than intermittently. The system maintains an ongoing analysis of user state and application context, with data streams from user interactions and application events flowing continuously into the context determination module. This continuous operation ensures that context information is always current and ready for immediate notification personalization, eliminating delays associated with batch processing or on-demand analysis
3Reliability
If the system delivers personalized context-rich notifications, then the coaching effectiveness and decision-making support improve, but the device complexity and implementation difficulty increase
Solution Approach 1:
The notification system is designed with universal components that can handle multiple functions. The context determination module serves both notification personalization and coaching generation functions. The same data processing infrastructure supports diverse notification types and coaching scenarios. This multi-functionality reduces implementation complexity by reusing proven components across different use cases rather than building separate specialized systems for each function
Solution Approach 2:
The system incorporates self-service mechanisms where the notification framework automatically adapts to different coaching scenarios and user needs without requiring manual configuration for each case. The context determination module autonomously analyzes incoming event data and user state information to generate appropriate notifications and coaching. This self-service capability reduces implementation burden by eliminating the need for extensive manual setup and customization while maintaining high coaching effectiveness
Data Source
AI summary
A realtime contextual event notification system that ingests events as streams from any authorized entity applies rules to the event streams, determines a context of an end-user who is a recipient of a targeted notification, and provides notifications to the end-user in accordance with the context. The event streams may come from multiple sources and rules may be applied to provide realtime contextual information associated with the end-user.