Cellular Call Classification Plugin for Accurate Billing
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Solution Overview
Problem
Current methods for distinguishing between business and personal cellular phone calls are inflexible, especially in roaming situations, and fail to support complex chargeback scenarios, leading to inaccurate billing and resource management issues.
Innovation Solution
A method and system that extends cellular phone capabilities to dynamically classify calls based on user location, time, or office interactions, allowing users to tag calls with specific reasons and profiles, enabling accurate billing without relying on centralized systems or operator-specific prefixes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a centralized billing system is used to distinguish between business and personal calls, then billing accuracy is improved, but server congestion and system complexity increase
Solution Approach 1:
The patent divides the call classification function into two segments: the mobile device determines whether a call is personal or business using local criteria (time, location, contact type), and the billing system simply processes the pre-classified calls. This segmentation eliminates the need for a complex centralized system to analyze call patterns, reducing server congestion while maintaining billing accuracy.
Solution Approach 2:
The mobile device performs call classification in advance before billing processing. By determining call type locally based on pre-configured criteria (business hours, location tags, contact categories), the system prepares billing information beforehand, eliminating the need for complex real-time analysis at the billing server and reducing system complexity.
2Measurement precision
If operator-specific personal call prefixes are used, then personal call identification is improved, but adaptability to different operators and roaming situations deteriorates
Solution Approach 1:
The patent implements a universal call classification mechanism that works across different operators and roaming scenarios. Instead of relying on operator-specific prefixes, the system uses generic criteria (time of day, location, contact type) that can be applied universally. The mobile device determines call type locally and tags it accordingly, making the solution operator-independent and suitable for international roaming.
Solution Approach 2:
The system changes the classification parameters from operator-specific prefixes to universal parameters such as time of day, geographic location, and contact category. These parameters can be adjusted based on user profiles and company policies, providing adaptability to different operators and roaming situations while maintaining accurate personal call identification.
3Measurement precision
If employees manually track and report personal calls, then billing accuracy is improved, but time consumption and operational complexity increase
Solution Approach 1:
The mobile device automatically performs call classification and tagging without requiring employee intervention. The device uses pre-configured user profiles containing personal and business contact information, along with location and time data, to automatically determine whether each call is personal or business. This self-service approach eliminates manual tracking while maintaining billing accuracy.
Solution Approach 2:
The system implements automatic feedback loops where the mobile device continuously monitors call parameters (time, location, contacted number) and automatically adjusts call classification based on user profiles and company policies. This automated feedback mechanism eliminates the need for manual employee reporting while ensuring accurate billing classification.
4Measurement precision
If detailed employee information is stored in centralized databases, then billing accuracy is improved, but information security risks and system complexity increase
Solution Approach 1:
The patent extracts sensitive employee information (contact lists, personal details, company policies) from centralized databases and stores it locally in the mobile device as user profiles. The mobile device uses this locally stored information to determine call classification, eliminating the need to transmit sensitive data to centralized servers. Only anonymized billing results are sent to the billing system, significantly reducing information security risks.
Solution Approach 2:
The system implements local processing of sensitive information by storing and using employee profiles, contact lists, and company policies directly in the mobile device. Each device operates independently with its own local data, eliminating the need for a centralized database containing detailed employee information. This local quality approach maintains billing accuracy while minimizing information security risks.
Data Source
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AI summary
A method and system is hereunder disclosed for managing phone calls on phone devices used by the employee of a company. When the phone device user wants to give a call, a new plugin (210) in the phone device interpretes an attribute value added by the phone device user to each phone number in order to categorize the call. The cell phone user enters a profile describing his call accounting information. The Call management plugin (210), using the user profile and the personal prefixing service supported by the phone networks computes a prefix for user personal calls which will be adapted to the user location. The Call management plugin (210) at the end of the call tags the Call information as "personal call" or "business call" and adds to the Call information some details of the user phone call accounting specificities. Later on, a new plugin (230) in the phone device will send the tagged call information to a remote server of the company which will be able to consolidate billing information received from the phone operators with the tagged call information. The company will also use the tagged call information to compute more detailed call accounting such as dispatching of business calls per employee business account.