Executable Action Modification for Schedule Conflict Resolution
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Solution Overview
Problem
Existing methods for accurately implementing software functions are often inaccurate and lack flexibility, requiring significant resources and time for generating replacement modification functions.
Innovation Solution
A method and system that detect changes in user schedules, determine alternative activities, and automatically execute additional actions using machine learning software to accommodate the alternative activities within the user's schedule, ensuring real-time execution and user preference alignment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If traditional software function implementation methods are used, then manufacturing precision is improved, but device complexity and resource consumption increase
Solution Approach 1:
The system automatically detects schedule changes, determines alternative activities, and executes additional actions without human intervention. The processor autonomously monitors calendar data, identifies conflicts, selects replacement activities based on user preferences, and modifies schedules, eliminating the need for complex manual software configuration and reducing system complexity.
Solution Approach 2:
The patent replaces traditional mechanical software modification processes with automated electronic detection and execution systems. Instead of manually generating replacement functions through complicated software processes, the system uses automated processors to detect changes, determine alternatives, and execute actions, significantly reducing resource consumption and complexity.
2Manufacturing precision
If traditional software function implementation methods are used, then manufacturing precision is improved, but loss of time increases
Solution Approach 1:
The system performs preliminary actions by pre-determining alternative activities and preparing replacement functions before schedule conflicts occur. The processor analyzes user preferences and available activities in advance, so when a schedule change is detected, the alternative is already prepared and can be executed immediately without time-consuming generation processes.
Solution Approach 2:
The automated system continuously monitors schedule data and automatically generates and executes replacement activities without requiring manual software intervention. This self-service approach eliminates the time-consuming process of manually creating modification functions while maintaining high implementation accuracy through automated detection and execution.
3Ease of operation
If automated schedule adjustment is implemented, then ease of operation is improved, but reliability may worsen due to user acceptance uncertainty
Solution Approach 1:
The system incorporates feedback mechanisms by analyzing user preferences, historical behavior patterns, and acceptance data to continuously improve its activity selection algorithms. The processor uses this feedback to determine which alternative activities are most likely to be accepted by the user, thereby maintaining high reliability while providing easy automated operation. User responses to proposed alternatives further refine the system's predictive accuracy.
Data Source
AI summary
A method for improving an action implementation process is provided. The method includes detecting a cancelation or a rescheduling for an originally planned activity of a user to be performed during a first time period. An alternative activity for replacement of the originally planned activity is determined. It is determined that a second time period necessary for performing the alternative activity exceeds the first time period and in response, an executable action is generated. The executable action is configured to be combined with the alternative activity such that the alternative activity may be accommodated. Machine learning software code is executed top determine if the user would be likely to accept the alternative activity if the additional executable action exceeds a specified threshold. In response, the executable action is automatically executed in real time thereby enabling the alternative activity.