<div> Gas pipeline networks are critical components of modern energy infrastructure, responsible for the safe and efficient transportation of natural gas from production facilities to end users. Ensuring the reliability, safety, and operational efficiency of these networks is a major challenge due to factors such as pipeline aging, corrosion, leaks, equipment failures, and external environmental impacts. Traditional monitoring and inspection methods often rely on periodic maintenance and manual assessments, which may be insufficient for detecting faults in real time and preventing operational disruptions. In recent years, intelligent monitoring and fault detection systems have emerged as advanced solutions for enhancing pipeline integrity and operational performance through the integration of Artificial Intelligence (AI), Machine Learning (ML), Internet of Things (IoT), sensor technologies, and real-time data analytics.&nbsp; </div> <div> <br> </div> <div> This study examines the role of intelligent monitoring and fault detection systems in gas pipeline networks, focusing on their applications in leak detection, anomaly identification, predictive maintenance, and infrastructure health monitoring. Advanced AI-driven models, including deep learning algorithms and pattern recognition techniques, are capable of analyzing large volumes of sensor and operational data to identify abnormal conditions and predict potential failures before they occur. The findings indicate that intelligent monitoring systems significantly improve fault detection accuracy, reduce response times, minimize operational downtime, and enhance overall pipeline safety. Furthermore, these technologies contribute to cost savings, environmental protection, and regulatory compliance by enabling proactive maintenance and risk management strategies. Despite these advantages, challenges such as data quality issues, cybersecurity risks, high implementation costs, and integration with legacy infrastructure remain significant barriers to adoption. The study concludes that intelligent monitoring and fault detection systems are essential for the development of resilient, efficient, and sustainable gas pipeline networks and highlights future research opportunities in digital twins, edge computing, and explainable artificial intelligence. </div>