The increasing integration of edge computing with cloud infrastructure has required efficient resource management and workload distribution in IoT-based edge cloud environments. Containerization has emerged as a promising solution for deploying and managing applications due to its lightweight and portable nature. However, seamless container migration between edge and cloud environments remains a challenge, especially in large-scale IoT networks, due to dynamic network conditions, resource constraints, and service availability concerns. This study proposes a fuzzy logic-based container migration approach for IoT-driven edge cloud systems. The primary objective is to develop a migration mechanism that enables efficient and adaptive container movement between edge devices and cloud infrastructure while optimizing system performance and resource utilization. The proposed approach considers hardware capabilities, network conditions, and containerization constraints to enhance service reliability and responsiveness. The key contributions of this research include an in-depth analysis of container migration challenges in edge cloud systems, the design of an intelligent migration mechanism, and a comprehensive evaluation of its performance under various workloads and network conditions. In addition, the study evaluates the cost effectiveness of the proposed solution compared to traditional deployment models and investigates load balance, fault tolerance, and workload optimization strategies.