Real-time Event Status via Enhanced GUI
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Solution Overview
Problem
Existing graphical user interfaces (GUIs) face challenges in efficiently navigating and accessing information associated with events to determine if they satisfy program criteria, leading to resource consumption and poor user experience.
Innovation Solution
A system that provides a GUI for generating records associated with events, allowing users to input information indicating whether the event satisfies program criteria, and utilizes a machine learning model to analyze this information in real-time, converting it into a standardized format for storage and generating an information package.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If users navigate to pages by entering addresses or clicking links to access event information, then users can obtain event status information, but this consumes device resources, server resources, and network resources
Solution Approach 1:
The system pre-loads and caches event status information in the browser before users need to access it. The event status determination logic is embedded in the page that generates the event record, so the information is prepared in advance and made immediately available without requiring additional navigation or resource consumption when users need it.
2Productivity
If the GUI includes fields for inputting event information to determine program criteria satisfaction, then real-time event status can be determined, but the device complexity increases
Solution Approach 1:
The event status determination fields are merged directly into the page that generates the event record. Instead of requiring separate navigation to determine status, the determination capability is combined with the record generation function, allowing users to input event information and immediately receive status determination without additional steps or complex navigation structures.
3Measurement precision
If a machine learning model analyzes event information to obtain status information, then accurate real-time analysis is achieved, but processing time and computational resources increase
Solution Approach 1:
The machine learning model for event status determination is pre-trained and embedded within the page that generates event records. The model is prepared in advance with all necessary processing capabilities, allowing it to analyze event information and determine status in real-time without requiring additional processing time or external computational resources when users need the results.
Data Source
AI summary
In some implementations, an event management device may generate a document object model (DOM) associated with a graphical user interface (GUI) that is associated with a platform to cause one or more fields to be included in the GUI. The event management device may provide, to the platform, the DOM to cause the GUI to be displayed. The event management device may receive, via the GUI, an indication of information associated with the event. The event management device may determine that the event satisfies the criteria based on the information received via the GUI. The event management device may store the information associated with the event in a database in connection with an identifier indicating that the event satisfies the criteria. The event management device may transmit an indication of the one or more metrics for display via a client device.