AI Event-Location Search Using Calendar and Geo-Location Context
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Solution Overview
Problem
The proliferation of cloud services and IoT devices has led to data fragmentation, making it difficult for users to quickly retrieve relevant data across multiple platforms, especially when they need it for specific events or locations, as current applications lack an integrated AI search capability to link user data with calendar events and geo-location.
Innovation Solution
An AI E/L search assistant that analyzes calendar and geo-location data to determine search requests without user input, searching semi-private metadata to provide event-location results, leveraging algorithms and digital assistants to deliver relevant data to the user.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If users search for data individually across all known digital connections, then data retrieval can be performed, but time lost increases and probability of not finding data timely increases
Solution Approach 1:
The system performs preliminary actions by proactively searching for and retrieving data before the user needs it. The AI assistant analyzes calendar events and location data to anticipate when and where data will be needed, initiating searches in advance across multiple cloud services and IoT platforms, thereby eliminating the need for users to manually search at the moment of need.
Solution Approach 2:
The AI assistant provides self-service by autonomously performing data retrieval operations without requiring active user participation. It automatically analyzes metadata, determines search requests, executes searches across fragmented digital connections, and delivers relevant data based on calendar events and location context, freeing users from manual search tasks.
2Adaptability or versatility
If applications track user events and locations separately, then data can be collected, but no integrated search capability exists to link data with calendar events and geo-location
Solution Approach 1:
The system merges previously separate functions by combining calendar event tracking, location data collection, and data search capabilities into a single integrated AI assistant. This unified system links fragmented digital connections to calendar events and geo-location context, enabling comprehensive data retrieval across multiple platforms through one coordinated operation.
Solution Approach 2:
The AI assistant achieves universality by performing multiple functions within a single system: analyzing calendar data, processing location information, determining search requests, executing searches across various cloud services and IoT platforms, and delivering contextualized results. This multi-functional approach eliminates the need for separate specialized applications.
Data Source
AI summary
A method for independent event or location based search, with steps of receiving, from a user, at least one of calendar data and geo-location data and analyzing the at least one of the calendar data and the geo-location data. Then determining, using the at least one of the analyzed the calendar data and the geo-location data, without instructions from the user, an event or location based search request and searching semi-private metadata and semi-private correlated metadata related to the user with the event or location based search request to determine an event-location result. Lastly, providing to the user the event-location result.