Resource Aggregation System for Real-Time Event Prioritization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current systems fail to provide real-time resource requirements for event execution, leading to inefficiencies in prioritization and resource allocation across multiple systems and entities.
Innovation Solution
A system that passively scans user activities, applications, and geolocation data to predict future resource needs by deploying bots to identify patterns and generate dynamic filtered event priority lists, aggregating data across users to provide accurate AI-driven recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If systems communicate between multiple systems and entities for event execution and analysis, then comprehensive data collection is achieved, but real-time response capability deteriorates due to system lag
Solution Approach 1:
The system segments the data collection and processing workflow into distinct components: event detection modules that capture user activities across multiple systems, priority determination modules that assess event importance, and resource requirement modules that calculate needed resources. This segmentation allows parallel processing of different event types, reducing overall system lag while maintaining comprehensive data collection from multiple sources.
2Measurement precision
If the system studies multiple user activities including applications, internet activities, fitness activities, geolocation activities, and beacon recognitions, then prediction accuracy improves, but system complexity increases
Solution Approach 1:
The system implements a universal event processing framework that handles multiple activity types (applications, internet activities, fitness activities, geolocation activities, and beacon recognitions) through common processing logic. The priority determination module and resource requirement module serve universal functions across all activity types, reducing system complexity despite the diversity of data sources being analyzed for accurate predictions.
3Measurement precision
If the system aggregates priority data across multiple users and creates groups, then data accuracy for AI analysis improves, but processing time increases
Solution Approach 1:
The system performs preliminary actions by pre-aggregating user data into groups based on common characteristics and pre-calculating priority metrics for different event types. This preliminary processing organizes data structures in advance, allowing the AI analysis to operate on pre-processed, accuracy-validated groups without incurring excessive processing delays during actual event prediction.
Data Source
AI summary
Embodiments of the present invention provide a positioned system for passive scanning and evaluation of various event execution of a user to use in combination for aggregation and categorization of resource requirements. The system integrates bots for user applications, geolocation, and beacons to determine event execution by the user. The system may extract and pull data into analytics to understand event patterning of the user. Furthermore, the system extracts priority event data from across multiple users for aggregation of the priority data into various categories of users to create groups and provide more accurate data for artificial intelligence analysis and filtering for user priorities.