In the field of mobile IoT systems, particularly the adaptability and performance of mobility models play a critical role in optimizing RPL, an essential aspect in acquiring reliable and efficient communication in resource-constrained and dynamic environments. RPL, developed for certain static sensor networks, suffered various challenges in mobile landscapes where node mobility affects energy efficiency, reliability, and network performance. Therefore, this survey seeks to compare and review several mobility models, including the RPGM, MMM, GMM, MRW, RDM, RWM, and RWP, to address such challenges. The research facilitates a comprehensive examination of the applicability, disadvantages, advantages, and characteristics of all mobility models in promoting the role of RPL-focused mobile IoT systems. The study focuses on the effects of node mobility on routing stability, network throughput, and energy consumption, identifying key factors influencing protocol adaptation in dynamic environments. Experimental methodologies are employed to assess RPL's performance under these models, and the results are critically compared to highlight the strengths and limitations of different mobility models in supporting mobile IoT networks. The findings underscore the importance of selecting appropriate mobility models for optimizing RPL performance, particularly in scenarios involving mobile nodes such as vehicular networks, smart cities, and emergency response systems. The paper concludes by suggesting future research directions, including protocol enhancements, hybrid mobility models, and the integration of artificial intelligence for more adaptive routing solutions in mobile IoT environments.