Event Management Device for Real-Time Data Delivery
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Solution Overview
Problem
Existing data delivery systems are unable to dynamically detect real-time events while maintaining optimal response time and high availability, leading to increased latency due to the heterogeneity of user data and various data sources.
Innovation Solution
An event management device that includes an event detector to identify events, a data extraction unit to extract relevant user data, and a rule manager to determine and execute actions based on predefined rules, with a machine learning engine for updating rule relevance scores and adapting actions in real-time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the data delivery system processes a huge volume of heterogeneous user data from various sources, then the system can provide comprehensive data delivery services, but the processing latency increases and response time deteriorates
Solution Approach 1:
The patent segments the monolithic data processing system into multiple specialized components: event detection module, rule evaluation module, and action execution module. Each component handles specific tasks independently, allowing parallel processing of heterogeneous user data without increasing overall latency. The segmentation enables the system to process different data types through optimized pathways.
Solution Approach 2:
The system performs preliminary actions by pre-compiling rules and pre-processing user data into standardized formats before actual data delivery operations. The rule engine pre-evaluates conditions and prepares action plans in advance, so when real-time data arrives, the system can execute responses immediately without extensive processing delays.
2Adaptability or versatility
If the system executes multiple applications requiring access to user data, then the system functionality is enhanced, but the computational resource consumption increases and availability decreases
Solution Approach 1:
The patent implements a universal rule engine that serves multiple applications and data delivery functions through a single centralized system. Instead of having separate processing logic for each application, the rule engine provides a common platform that handles diverse data processing requirements, reducing overall computational resource consumption while maintaining high system availability.
Solution Approach 2:
The event detection module acts as an intermediary between various applications and the user data storage system. It centralizes access to user data, filters and validates events, and coordinates rule evaluation across multiple applications. This intermediary layer reduces redundant data access, minimizes computational overhead, and maintains system availability by preventing resource exhaustion.
3Loss of information
If the system maintains user data in storage structures and retrieves additional data from heterogeneous sources, then data completeness is improved, but the complexity of data management increases and response time decreases
Solution Approach 1:
The system implements dynamic data retrieval strategies that adapt to the specific event being processed. The event detection module dynamically determines which data sources to query based on the event type and existing user data completeness. This dynamic approach ensures data completeness is achieved only when necessary, reducing overall system complexity while maintaining response time performance.
4Productivity
If the system processes data with high computational performance, then the data delivery speed is improved, but the system complexity increases
Solution Approach 1:
The patent replaces complex mechanical data processing systems with an event-driven architectural model. Instead of continuous polling and manual data retrieval mechanisms, the system uses event detectors that automatically trigger rule evaluations and action executions. This substitution simplifies the system architecture while maintaining high data delivery speed through automated, event-triggered processing flows.
Data Source
AI summary
Embodiments of the invention provide an event management device for managing events comprising an event detector configured to detect the occurrence of an event related to data delivered by a data delivery system and to extract user data related to the detected event from a user data storage, the extracted user data comprising user data stored in at least one entry of the user data storage. The event management device further comprising a rule manager configured to determine one or more actions to be executed by applying one or more rules using the extracted user data, the event management device being configured to trigger execution of at least one determined action. The system may further dynamically update the rules using feedback data received for the executed actions.