The increasing complexity of IoT networks, particularly in critical domains such as e-health, intelligent transportation systems, and industrial environments, requires the implementation of adaptive routing strategies capable of ensuring high levels of quality of service (QoS). Although the Software-Defined Networking (SDN) paradigm offers centralized control and global network visibility, most existing controllers, such as Ryu, still rely on static routing mechanisms that are not well suited to the dynamic behavior of network traffic. In this context, we propose a dynamic QoS-oriented routing model for SD-IoT environments. This model assigns weights to network links based on several key metrics, including latency, link load, packet loss rate, and available bandwidth. It then uses the Dijkstra algorithm to compute the most suitable paths in real time. This approach allows the SDN controller to make context-aware routing decisions that account for both network topology and traffic characteristics. The model was evaluated through a series of scenarios that simulate three representative traffic types: e-health, transportation, and industrial. These scenarios involved progressively increasing load conditions. The results demonstrate significant improvements in performance, including reduced latency, lower packet loss, more balanced traffic distribution, and more efficient use of hardware resources at the switch level. These findings confirm the relevance and effectiveness of our approach and suggest promising perspectives for scalable, context-sensitive routing in SD-IoT networks.