Geography-Based Wireless KPI Analysis for Multi-Location Reporting
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Solution Overview
Problem
Conventional systems for determining wireless network performance metrics (KPIs) at multiple locations are time-consuming and require repeated enabling of multiple KPI layers, lacking the ability to analyze KPIs at multiple locations simultaneously.
Innovation Solution
A geography-based KPI analysis system that stores KPI configurations, color ranges, and metadata in a database, allowing for iterative determination of KPI values using latitude and longitude inputs, generating reports without repeatedly enabling KPI layers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple KPI layers are enabled for analyzing wireless network performance at multiple locations, then measurement precision is improved, but loss of time increases due to time-consuming enabling process and repeated operations
Solution Approach 1:
The system pre-configures and stores KPI layer settings in advance within the processing system. When analysis is required, the pre-configured KPI layers are automatically activated without manual re-enabling, significantly reducing the time loss while maintaining measurement precision across multiple locations
Solution Approach 2:
The processing system automatically manages the activation and configuration of KPI layers based on stored configurations. The system serves itself by automatically retrieving and applying the appropriate KPI settings without requiring repeated manual intervention to enable layers, thus eliminating time-consuming operations
2Measurement precision
If conventional systems analyze KPIs at multiple locations, then measurement precision is improved, but device complexity increases due to multiple KPI layers and repeated processing
Solution Approach 1:
The system segments the KPI analysis functionality into separate, pre-configured layers that are stored independently. Each KPI layer is a distinct module that can be automatically retrieved and applied as needed, reducing the complexity of managing multiple KPI configurations while maintaining the ability to analyze at multiple locations
Solution Approach 2:
The processing system is designed with universal functionality to handle multiple KPI types and locations through a single integrated framework. The system can retrieve and process different KPI configurations from stored data without requiring separate complex processing paths for each KPI type or location, thereby reducing overall device complexity
3Reliability
If conventional systems check KPI values again, then reliability is improved, but loss of time increases due to repeated enabling of KPI layers
Solution Approach 1:
KPI layer configurations are pre-stored in the processing system before actual verification is needed. When reliability checks are performed, the system retrieves the pre-configured KPI layers instantly rather than re-enabling them, allowing repeated verification of KPI values without time loss while maintaining reliability
Data Source
AI summary
Embodiments herein disclose a method and a geography based KPI analysis system for determining geography based KPI of a wireless network. The method includes receiving, by the geography based-KPI analysis system, a data point input comprising latitude and longitude information for which a geography based-KPI analysis report need to be generated. The method further includes determining the geography of the wireless network based on the latitude and longitude information. The method further includes for each KPI of the plurality of KPIs supported by the geography based-KPI analysis system for the geography, iteratively determining a KPI value based on the geography based-KPI color range and the geography image metadata. The method further includes generating the geography based-KPI analysis report comprising the KPI value for each KPI of the plurality of KPIs supported by the geography based-KPI analysis system for the geography.


