UAV-assisted federated learning with hybrid LoRa P2P/LoRaWAN for sustainable biosphere

Abstract

The increasing amount of data sensors generate, and the dynamic nature of climate and environment pose challenges for conventional smart environmental monitoring systems. These systems encounter difficulties in long-distance data communication, accurate data processing, and generalized prediction modeling, particularly in large-scale, remote, and hard-to-reach areas. Moreover, they are costly, complex, and inefficient, especially in regions with limited telecommunications infrastructure. Consequently, there is a pressing need for more efficient and effective monitoring techniques to safeguard natural resources and ecosystems. To address these challenges, we propose the concept of a novel environmental monitoring system that integrates aerial access networks (AAN), federated learning (FL), and hybrid LoRa Point-to-Point (P2P)/LoRaWAN technologies. This integration offers a reliable and efficient solution for monitoring remote regions. We provide an overview of the AAN, FL, and aerial FL paradigms and discuss the benefits and challenges of their integration. Preliminary simulation results demonstrated the proposed system’s feasibility and effectiveness. Lastly, we outline open challenges and potential research directions to advance this field.