Automated system for operator certification testing with geo-dependent test scripts and protocol analysis

Abstract

An automated system (100) for carrier certification testing, comprising: (a) a geo-dependent test script generation module configured to dynamically generate test scripts based on geographical data, network parameters and environmental conditions; (b) an execution module configured to automatically deploy and execute the test scripts on an operator's network infrastructure to evaluate key performance indicators such as latency, throughput, coverage and network availability; c) a log analysis module configured to collect, analyze and interpret real-time performance data from the network, detect anomalies and generate actionable diagnostic insights using machine learning algorithms; (d) a reporting module configured to automatically compile test results into certifiable reports highlighting compliance with predefined standards; and (e) a customisable scenario configuration interface allowing users to simulate different operating conditions, such as peak traffic, signal degradation and fluctuations in user density; f) the system enables end-to-end automation of carrier network testing, diagnostics and certification with minimal human intervention.

Description

[0001] The present invention relates to the development of an automated system for operator certification testing that utilizes geo-dependent test scripts and protocol analysis. It integrates location-based data to improve testing efficiency and accuracy for network services. The system enables real-time performance monitoring, diagnostics, and validation of operator networks.

[0002] In modern telecommunications, operator certification is a critical yet complex process that ensures that network services meet required performance and regulatory standards before deployment. Traditionally, this process relies heavily on manual testing, static scripts, and region-independent methods, which often lead to inefficiencies, inaccuracies, and delayed certifications—especially in geographically diverse environments. These conventional methods do not account for site-specific variables such as terrain, signal interference, and user density, resulting in incomplete or misleading network assessments. The invention closes this gap by introducing an automated, geo-dependent testing system that not only adapts test scripts based on local conditions but also uses real-time protocol analysis to identify issues and suggest immediate fixes.This significantly improves test accuracy, reduces time and cost, and enables network operators to deploy reliable and high-performance networks faster and more efficiently.

[0003] One objective of the present disclosure is to automate testing procedures, thereby reducing the time required to certify carriers.

[0004] Another objective of this disclosure is to adapt tests based on geographic data to ensure accurate performance assessments.

[0005] Another objective of this disclosure is to provide immediate feedback and troubleshooting recommendations to promptly resolve network issues.

[0006] Another objective of the present disclosure is to reduce human error and ensure more reliable, data-driven test results.

[0007] Another objective of the present disclosure is to minimize manual labor and reduce operational costs associated with network testing and certification.

[0008] Another objective of the present disclosure is to be adaptable to both small regional and large national networks in order to meet the different requirements of operators.

[0009] Another objective of this disclosure is to use machine learning to predict potential network performance issues, enabling proactive maintenance.

[0010] Another objective of this disclosure is to generate detailed, automated certification reports for thorough analysis and verification of conformity.

[0011] The present invention relates to geo-dependent test scripts that are dynamically generated based on location-specific data such as network topology, signal strength, and environmental factors. This adaptation ensures that the tests are relevant to the region being evaluated and provide accurate and realistic performance metrics.

[0012] Another embodiment of the present invention is that the system automates the operator certification process, reducing the need for manual intervention and accelerating the testing cycle. By performing a series of predefined and geo-dependent tests, the system evaluates key network parameters such as coverage, latency, and throughput to ensure compliance with industry standards.

[0013] Another embodiment of the present invention is that the system collects and analyzes performance data from the network during testing, using advanced analysis techniques such as machine learning.

[0014] Another embodiment of the present invention is that the system provides immediate feedback on network problems detected during testing through real-time diagnostics.

[0015] Another embodiment of the present invention is that after the tests are completed, the system generates automated, detailed reports summarizing the performance of the network.

[0016] Another embodiment of the present invention enables flexible test configurations where users can simulate a range of network conditions, including different user loads, traffic patterns, and environmental settings.

[0017] A further embodiment of the present invention is that the system is scalable and modular, making it suitable for both small regional networks and large, nationwide carrier infrastructures.

[0018] Another embodiment of the present invention is that the system can predict future network performance trends based on historical test data using integrated machine learning algorithms.

[0019] The present invention relates to an automated system for streamlining operator certification testing through the use of geo-aware test scripts and advanced log analysis. It ensures accurate network performance assessment through real-time diagnostics and customized test scenarios. The system consists of four key modules: geo-aware test script generation, automated test execution, real-time log analysis, and comprehensive reporting. Together, these modules enable faster and more accurate network certification and proactive troubleshooting. Geo-based test script generation

[0020] The invention begins with the creation of geo-aware test scripts, which are dynamically generated based on the geographical location of the network under test. These scripts adapt to the varying network conditions, topography, and infrastructure of different regions. By incorporating location-specific data such as signal strength, environmental factors, and user density, the system adapts the testing process to ensure a realistic analysis of network behavior. This module ensures that the tests are relevant to the specific network conditions of operators in different geographical locations, optimizing the accuracy and relevance of the test results. Automated carrier certification tests

[0021] The core functionality of the invention revolves around the automation of operator certification tests. The system uses geo-dependent test scripts to perform a comprehensive suite of tests on the operator's network infrastructure. This automation reduces human errors, minimizes manual effort, and accelerates the certification process. Key performance indicators (KPIs) such as latency, throughput, coverage, and network availability are evaluated. By eliminating manual testing procedures, the system significantly increases testing speed and reduces operating costs, ensuring timely network certification for network operators. Protocol analysis and performance monitoring

[0022] Once the geo-dependent test scripts are executed, the system collects comprehensive logs detailing network performance during each test. These logs are processed and analyzed in real time to detect anomalies, network outages, or performance degradations. Advanced analytics techniques, including machine learning algorithms, are applied to identify patterns and correlations in the network data. The system can pinpoint specific problem areas, such as low signal strength or bandwidth congestion, providing insight into network vulnerabilities that require attention. Real-time diagnostics and troubleshooting

[0023] Real-time diagnostics is a critical feature of the invention, allowing network engineers to immediately identify problems during the testing phase. While the geo-dependent test scripts are running, the system provides live feedback on network performance and offers detailed diagnostics of errors, outages, or service interruptions. The system's AI-driven analysis recommends corrective actions and enables technicians to take immediate steps to resolve issues. This proactive approach not only improves the testing experience but also contributes to faster problem resolution and ensures that network certifications meet the desired standards. Comprehensive reports and insights

[0024] The invention provides a robust reporting module that compiles all test results and performance data into comprehensive reports. These reports include visualizations, summaries of key metrics, and detailed logs, making it easier for stakeholders to understand network performance. The system automatically generates certification reports that highlight areas that do or do not meet certification standards. Furthermore, it provides insights into long-term performance trends, enabling network operators to track network health over time and make data-driven decisions for network optimization and planning. Customizable test configurations and scenarios

[0025] The invention supports highly customizable test configurations, allowing users to design and simulate various network scenarios based on specific requirements. The system offers flexibility in test configuration, whether testing peak-hour performance, stress testing under heavy load conditions, or simulating low-signal environments. Users can configure parameters such as user load, traffic patterns, and geographic coverage to match real-world conditions. This customization ensures that tests are aligned with the network operator's individual network development and operational goals. Scalable integration and deployment

[0026] Finally, the system is designed for scalable integration and deployment across multiple carrier networks. Whether testing a small regional network or a large nationwide infrastructure, the system can be scaled to handle varying levels of complexity. It integrates seamlessly into existing carrier systems, ensuring minimal disruption to ongoing operations. Its modular design allows for the easy addition of new test cases, scenarios, and analysis tools as network technologies evolve, allowing the system to adapt to future advances in network infrastructure and testing methods.

[0027] The invention is explained again below with reference to the figure. It shows: Fig. : an automated system (100) for operator certification testing using geo-dependent test scripts and protocol analysis.

[0028] Fig. illustrates an automated system (100) for operator certification testing that utilizes geo-dependent test scripts and protocol analysis. Operation of the system begins with the creation of geo-dependent test scripts tailored to the specific geographic region in which the network will be deployed. The system collects location-related data, including network topology, signal strength, and environmental factors, to customize the testing process. Once the geo-dependent test scripts are created, they are automatically executed on the operator's network infrastructure. These tests evaluate various performance parameters such as network coverage, latency, throughput, and availability to assess the operator's compliance with certification standards. The tests are designed to simulate real-world network conditions to ensure that the results are both accurate and relevant to the region being tested.

[0029] During the testing process, the system continuously collects logs and performance metrics, which are analyzed in real time. Advanced protocol analysis techniques, including machine learning, are used to detect anomalies, outages, and potential network performance issues. Any deviation from expected behavior triggers alerts, and the system provides diagnostic feedback to determine the root cause of problems. Troubleshooting recommendations are provided in real time, allowing network engineers to quickly resolve issues. Finally, the system compiles all test results and diagnostics into comprehensive reports that summarize network performance, highlight areas for improvement, and ensure that the operator's network meets the required certification standards.This streamlined, automated process improves efficiency, reduces human error, and accelerates network certification.

Claims

[1] An automated system (100) for carrier certification testing, comprising: (a) a geo-dependent test script generation module configured to dynamically generate test scripts based on geographical data, network parameters and environmental conditions; (b) an execution module configured to automatically deploy and execute the test scripts on an operator's network infrastructure to evaluate key performance indicators such as latency, throughput, coverage and network availability; c) a log analysis module configured to collect, analyze and interpret real-time performance data from the network, detect anomalies and generate actionable diagnostic insights using machine learning algorithms; (d) a reporting module configured to automatically compile test results into certifiable reports highlighting compliance with predefined standards; and (e) a customisable scenario configuration interface allowing users to simulate different operating conditions, such as peak traffic, signal degradation and fluctuations in user density; f) the system enables end-to-end automation of carrier network testing, diagnostics and certification with minimal human intervention. [2] The system (100) of claim 1, wherein the geographic test script generation module incorporates signal strength heatmaps and topographic data to simulate realistic network environments [3] The system (100) of claim 1, wherein the execution module supports concurrent testing in multiple regions to simultaneously validate the performance of carriers in different geographic locations. [4] The system (100) of claim 1, wherein the log analysis module applies supervised machine learning models to classify performance problems and predict future network outages. [5] The system (100) of claim 1, wherein the reporting module supports visual dashboards and exports to standardized formats such as PDF, CSV, and JSON for regulatory submission. [6] The system (100) of claim 1, wherein the scenario configuration interface enables drag-and-drop test case design and parameter tuning for user-defined simulation settings. [7] The system (100) of claim 1, further comprising an alerting mechanism that notifies network administrators of critical failures or threshold violations during test execution in real time.

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