Review of Self-Healing Iot Networks based Ai-Driven Fault Detection and Recovery

This study explores the capability of self-healing in Internet of Things (IoT) networks through the application of artificial intelligence (AI) techniques for fault detection and recovery. By leveraging deep learning and machine learning methods, the research investigates automated processes that diagnose and rectify network issues in real-time, ensuring reliable communication within interconnected environments. The findings highlight how these AI-driven approaches enhance network resilience and operational efficiency, reducing downtime and minimizing the need for human intervention. Furthermore, the study examines the implications of integrating AI in IoT architectures, demonstrating significant improvements in fault tolerance. The results underscore the transformative potential of AI in the management of complex IoT systems, paving the way for more robust and adaptive network solutions.