Automated Toll Calling to EAS Migration via Regression Analysis
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Solution Overview
Problem
The manual process of converting a toll calling area to an extended area service (EAS) is time-consuming and inefficient, requiring extensive data collection and resource forecasting, which hampers a smooth transition and timely implementation.
Innovation Solution
A computer system and method that calculates telephone call information and expected growth to provide outputs for resource determination and migration planning, utilizing customer data and regression analysis to automate the conversion process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual data collection and resource forecasting is used for converting toll calling area to EAS, then accuracy of resource determination is improved, but engineering time and implementation efficiency deteriorate
Solution Approach 1:
The patent replaces manual mechanical data collection and analysis processes with automated computer-based systems. The system automatically collects customer calling data, performs regression analysis, and generates resource determination outputs without manual intervention, thereby maintaining accuracy while dramatically reducing engineering time.
Solution Approach 2:
The system enables self-service by automatically performing data collection, analysis, and resource forecasting functions that previously required manual engineering effort. The computer system autonomously processes customer data and generates the necessary outputs for EAS conversion without requiring manual resource forecasting procedures.
2Loss of information
If manual process is used for EAS conversion, then detailed analysis of customer data is improved, but information flow and transition smoothness deteriorate
Solution Approach 1:
The computer system performs multiple functions including data collection, regression analysis, resource forecasting, and report generation within a single integrated platform. This multi-functional approach ensures comprehensive customer data analysis while improving information flow and transition efficiency compared to separate manual processes.
Solution Approach 2:
The system replaces manual data analysis mechanisms with automated computer-based regression analysis and processing. This substitution maintains the ability to perform detailed customer data analysis while significantly improving information flow and reducing transition friction through automated workflows.
3Productivity
If automated computer system is used for EAS conversion, then engineering time and productivity are improved, but complexity of implementation increases
Solution Approach 1:
The patent introduces a computer-based intermediary system that mediates between raw customer data and resource determination requirements. This automated system handles the complexity of data processing, regression analysis, and forecasting internally, presenting simplified outputs to users while maintaining high productivity and reducing engineering time.
4Measurement precision
If traditional manual forecasting methods are used, then resource allocation accuracy is improved, but transition time and implementation efficiency deteriorate
Solution Approach 1:
The system replaces manual resource forecasting mechanisms with automated computer-based regression analysis and data processing. This substitution maintains resource allocation accuracy by using rigorous statistical methods while dramatically reducing transition time and improving implementation efficiency through automation.
Solution Approach 2:
The computer system performs preliminary data collection, analysis, and forecasting actions automatically before the actual EAS conversion is needed. This preliminary automated processing ensures accurate resource allocation is prepared in advance, reducing the time required for actual transition implementation.
Data Source
AI summary
Converting a toll calling area to an extended area service (EAS) is provided. The present invention allows customer, regional, and equipment data to be collected into a computing device with a set of assumptions. The data is processed using calculations, regression analysis, and statistics to provide a migration plan in an automatic manner. Results may be derived from the various information detailing an impact of migrating to an EAS.


