Messaging Availability Prediction Using Calendar and Location Data
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Solution Overview
Problem
Existing messaging applications have limited and inaccurate availability status options, as users must manually update their status, leading to inconsistencies and an inability to accurately represent their availability for communication.
Innovation Solution
A method and system that calculate and display a numerical availability status based on historical usage data, location data, and calendar data using machine learning and data analytics, providing both current and predicted future availability status, which are automatically updated and visually represented to other users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users manually set availability status from predefined options, then the system is simple to operate, but the accuracy of availability representation deteriorates
Solution Approach 1:
The system automatically determines availability status by analyzing multiple data sources including calendar events, location information, and usage patterns without requiring manual user input. The processor continuously monitors these data sources and autonomously updates the availability status, eliminating the need for users to manually select from predefined options while maintaining high accuracy through objective data-driven assessment.
Solution Approach 2:
The system transitions from discrete predefined availability categories to a continuous numerical availability score ranging from 0 to 100. This parameter change allows for more granular and accurate representation of availability states, enabling the system to reflect subtle variations in user availability that predefined categories cannot capture.
2Reliability
If availability status is updated manually by users, then the system requires minimal processing resources, but the reliability of availability information deteriorates
Solution Approach 1:
The system leverages existing multi-functional data sources already present in user devices, such as calendar applications, location services, and usage tracking mechanisms. By repurposing these existing components for availability determination, the system achieves reliable automatic updates without requiring entirely new specialized hardware or complex dedicated systems.
Solution Approach 2:
The system implements continuous monitoring of multiple data sources and dynamically adjusts availability status based on real-time changes in calendar events, location, and usage patterns. This feedback mechanism ensures that availability information remains reliable and up-to-date, automatically responding to changes in user context without manual intervention.
3Loss of information
If basic predefined availability options are provided, then the user interface is simple, but the information completeness deteriorates
Solution Approach 1:
The system segments availability determination into multiple independent data dimensions including calendar events, location information, usage patterns, and time-based factors. Each data source contributes a specific aspect of availability information, and the processor integrates these segmented data elements to form a comprehensive availability assessment, preventing information loss while maintaining manageable system complexity.
Solution Approach 2:
The system adds temporal dimension to availability representation by providing both current availability status and predicted future availability. This dimensional expansion allows users to understand not only present availability but also anticipated availability at future time points, significantly enhancing information completeness without proportionally increasing system complexity.
Data Source
AI summary
Methods, systems and computer program products for determining and providing an availability status of an individual in a messaging application are provided. Aspects include obtaining historical usage data for the individual for the messaging application, obtaining location data, activity data and calendar data for the individual, and calculating a current availability status for the individual based on the historical usage data, the location data, the activity data and the calendar data. Aspects also include calculating a predicted future availability status for the individual based on the historical usage data, the location data, the activity data and the calendar data and providing the current availability status and the predicted future availability status to other users of the messaging application.