Automated Event Scheduling Using Geofenced Participant Filtering
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Solution Overview
Problem
Event scheduling is typically conducted manually, which is labor-intensive and prone to errors and inefficiencies, especially when identifying participants and attendees.
Innovation Solution
An enterprise computer server system aggregates geographic location and profile data to identify members of a target population group (TPG) who can participate in an event, using virtual geofences and occupational filtering rules to streamline the scheduling process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If event scheduling is conducted manually by one or more persons, then flexibility in organizing events is maintained, but the process becomes labor-intensive, highly inefficient, and prone to mistakes and errors
Solution Approach 1:
The system enables self-service by automatically identifying suitable participants and attendees for events based on profile data and geographic location, eliminating the need for manual scheduling efforts. The automated participant identification system performs the scheduling function independently using stored data and predefined criteria.
Solution Approach 2:
The patent replaces the mechanical manual process with an automated computer-based system that uses data processing algorithms to identify participants. The system substitutes human effort with automated computational methods that query profile data and geographic information to generate participant lists.
2Loss of time
If manual methods are used to identify participants and attendees, then human judgment can be applied, but the process becomes highly inefficient and time-consuming
Solution Approach 1:
The system performs preliminary actions by pre-storing profile data and geographic location information in databases before events are scheduled. This advance preparation allows the automated system to quickly query and identify suitable participants without time-consuming manual research when events need to be organized.
Solution Approach 2:
The system creates copies of participant profiles and geographic data in structured database formats, allowing rapid retrieval and analysis. Instead of manually examining individual records, the system efficiently queries copied and organized data to identify participants matching event criteria.
3Reliability
If automated systems are implemented to streamline event scheduling, then efficiency and accuracy improve, but data aggregation and processing complexity increase
Solution Approach 1:
The system segments the participant identification process into distinct functional modules: geographic location filtering, profile data querying, and participant list generation. This segmentation allows each component to handle specific data processing tasks independently, improving reliability while managing complexity through modular design.
Solution Approach 2:
The system introduces intermediary databases that store and organize profile data and geographic information, acting as mediators between the automated scheduling system and the raw data sources. These intermediary structures simplify data access and processing while ensuring accurate participant identification.
Data Source
AI summary
An enterprise computer server system, a computer program product, and a computer-implemented method to automate event scheduling based on geographic location data and profile data of a target population group (TPG).