“…• Models can be complex and computationally expensive to train values provide a longer range but lower data rates and energy consumption, while lower SF values offer higher data rates but a shorter range [63]. In addition, LoRaWAN networks experience dynamic changes in device density, traffic patterns, and environmental factors due to many factors like urbanization [64]. In order to optimize network performance, adaptive resource allocation mechanisms are required to account for these dynamic conditions in real time.…”