Automated Network Self-Healing via AI Fault Mapping
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Solution Overview
Problem
Complex communication networks with numerous cell site nodes face challenges in automated detection, diagnosis, and correction of issues, leading to inefficient and ineffective documentation and trouble handling, especially in uncontrolled environments with high failure probabilities.
Innovation Solution
An automated system that searches databases for failure conditions, maps faults to solutions, and deploys corrective configurations via Over The Air updates, minimizing human intervention and recording solution efficacy for self-healing networks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual detection, diagnosis and correction methods are used in complex communication networks, then human operators can handle problems with judgment and adaptability, but the documentation and trouble handling processes become inefficient, ineffective and unresponsive due to labor intensive efforts and inability to perfectly capture and track numerous variables
Solution Approach 1:
The system enables automated self-service through AI/ML models that independently detect, diagnose, and correct network issues without human intervention. The platform automatically captures numerous variables including specific location, mobile device, user application, and time of day, processes them through machine learning algorithms, and deploys corrective configurations via Over The Air updates, eliminating labor-intensive manual processes while maintaining high effectiveness in handling complex network troubles
Solution Approach 2:
The patent replaces manual mechanical processes with automated digital systems. Human operators manually documenting and tracking problems are substituted by an automated platform that uses sensors, databases, and AI/ML algorithms to detect, analyze, and resolve issues. The system electronically captures and processes numerous variables that are difficult for humans to track, transforming manual trouble handling into an efficient automated digital workflow
2Productivity
If the number of cell site nodes is increased to satisfy growing network demand, then network capacity and coverage are improved, but the increasing probability and volume of cell site node failures drive the resources for more resources to manage detection, diagnosis and correction
Solution Approach 1:
The system implements continuous feedback loops where sensors monitor cell site node conditions in real-time, AI/ML models analyze the data to detect early signs of failures, and corrective actions are automatically deployed. The platform tracks the efficacy of applied solutions and uses this feedback to continuously improve detection and diagnosis accuracy, enabling the network to handle increased capacity while maintaining reliability through proactive failure prevention
Solution Approach 2:
The platform performs preliminary actions by predicting potential failures before they occur. AI/ML models analyze historical data and current sensor readings to identify patterns indicating impending failures, allowing the system to deploy preventive corrective configurations before actual failures happen. This proactive approach enables the network to scale capacity while reducing the volume of actual failures through early intervention
3Speed
If automated systems are implemented to detect and correct network issues, then response time and consistency are improved, but the complexity of matching each problem with the associated cell site condition and determining successful solutions increases
Solution Approach 1:
The patent implements a universal automated platform that handles multiple functions including detection, diagnosis, correction, and verification of network issues. The AI/ML models are designed to recognize patterns across different cell site conditions and problem types, enabling a single system to manage the complexity of matching various problems with appropriate solutions. The platform's multi-functional architecture simplifies the overall system by consolidating what would otherwise require multiple separate complex systems
Data Source
AI summary
Prediction, detection and mitigation of network or device issues in a communication system are facilitated. An embodiment can comprise: determining whether an identified problem of a device has an associated defined solution stored in a repository of information; transmitting solution information representative of the associated defined solution to the device for application of the solution information to the device in a manner determined to have less than a defined amount of impact on the device and in accordance with defined security protocols of the device; and assessing a performance of the device after application of the solution information to the device to determine whether the solution information solved the identified problem. In some embodiments, solution detection can be performed such that based on a determination that the identified problem has been removed, the change that caused the identified problem can be determined.