Large-scale Internet of Things deployments demand long-range wireless communications, especially in urban and metropolitan areas. LoRa is one of the most promising technologies in this context due to its simplicity and flexibility. Indeed, deploying LoRa networks in dense Internet of Things scenarios must achieve two main goals i.e., efficient communications among many devices and resilience against dynamic channel conditions due to demanding environmental settings like the presence of many buildings. The project work investigates adaptive mechanisms to configure the communication parameters of LoRa networks in dense IoT scenarios and developed an open-source framework for end-to-end LoRa simulations. We then implement and evaluate LoRa to dynamically manage link parameters for scalable and efficient network operations. Our proposed solution significantly increases both the reliability and the energy efficiency of communications over a channel, almost irrespective of the network size. To show that the delivery ratio of very dense networks can be further improved by using a network-aware approach, wherein the link parameters are configured based on the global knowledge of the network