The surge in Internet of Things (IoT) controller mobile applications, particularly for smart lighting systems, underscores the need for robust quality assurance to manage their complexity. This study explores Model-Based Testing (MBT) using the Extended Finite State Machine (EFSM) approach on the Wiz Connected App, an IoT mobile controller. Utilizing the TestOptimal tool with the Postman Problem algorithm as the optimal sequencer, the research achieved 100% coverage of states, transitions, and acceptance criteria. Despite this success, the MBT approach for IoT systems demonstrated higher complexity and longer execution times compared to web applications in similar research. The dynamic characteristics of IoT systems, including interaction complexity and real-time behavior, are effectively addressed through MBT, enhancing the robustness and reliability of the system. Future research should focus on integrating hardware testing with MQTT, enhancing sensor feature inclusion for real-time interactions, and exploring algorithms that reduce execution times while maintaining test coverage. Additionally, optimizing EFSM models to reduce cyclomatic complexity can streamline and scale MBT frameworks, making them more feasible for complex IoT environments. These advancements aim to enhance MBT methodologies, addressing the dynamic challenges of IoT systems and extending their benefits across broader IoT applications.