IoT Enhanced Resilience: Advanced AI Technique for Leak Detection and Predictive Maintenance in Oil and Gas Pipeline

The study seeks to investigate how the implementation of IoT-driven advanced AI methods can bolster the robustness of oil and gas pipelines by improving strategies for detecting leaks and conducting predictive maintenance. The implementation of IoT in oil and gas pipelines poses challenges, such as the need for strong cybersecurity measures to safeguard sensitive data, addressing complexities in integrating IoT devices and advanced AI technologies, and requiring seamless coordination among diverse components, potentially leading to difficulties in compatibility, interoperability, and overall system integration. Addressing the obstacles in deploying IoT for oil and gas pipelines involves utilizing advanced AI methods like federated learning to enhance data privacy and adopting a modular integration approach, offering solutions to ensure strong cybersecurity, smooth coordination, and enhanced compatibility and interoperability throughout the infrastructure. Overcoming challenges in implementing IoT for oil and gas pipelines includes the application of advanced AI techniques, such as federated learning for improved data privacy, and adopting a modular integration strategy, providing solutions to ensure robust cybersecurity, seamless coordination, and increased compatibility and interoperability across the infrastructure.