AI-enabled Joint Sensing and Communication for the Internet of Drones

The Internet of Drones (IoD) is an emerging paradigm where networks of Unmanned Aerial Vehicles (UAVs) collaborate to perform tasks in dynamic, infrastructure-limited environments. UAVs are increasingly deployed in disaster response, environmental monitoring, precision agriculture, and smart city applications due to their mobility, flexibility, and rapid deployment capabilities. These applications rely heavily on real-time data exchange and autonomous coordination, placing stringent demands on the underlying network infrastructure. At the same time, advances in wireless communication (e.g., 5G/6G, Wi-Fi 6/7), mobile sensing, and artificial intelligence (AI) have opened new opportunities to design intelligent UAV systems that can perceive, communicate, and act efficiently in complex environments.;;Research Gap:;Despite significant advancements in both drone technologies and wireless communication protocols, current IoD systems often treat sensing, communication, and control as separate layers, resulting in suboptimal performance. Existing architectures typically lack adaptive feedback between sensing inputs and communication behaviour. Moreover, while AI has been widely adopted in perception and control, its potential to drive adaptive, context-aware networking in UAV fleets remains underexplored. There is also limited work on how mobile computing and RF-based sensing can be jointly leveraged to optimise network-level decisions in real time.;;Aim:;This project aims to develop an AI-enabled framework for the joint design of sensing and communication in UAV networks. The overarching goal is to create intelligent, resilient, and scalable IoD architectures that integrate mobile computing, wireless sensing, and AI to support autonomous, collaborative drone operations in diverse scenarios.;;Objectives:;- To investigate how mobile computing and RF-based sensing (e.g., signal strength, CSI, mobility patterns) can inform adaptive communication strategies in UAV networks.;- To design AI-driven models for real-time perception, network optimisation, and autonomous decision-making across multi-UAV systems.;- To develop and evaluate joint communication–sensing protocols over next-generation wireless technologies, including Wi-Fi 6/7 and 5G/6G.;- To prototype and test the proposed system using a real-world UAV testbed with edge/cloud capabilities.;- To explore forward-looking concepts such as the Quantum Internet of Drones, examining how classical Internet principles can be adapted to support ultra-secure and low-latency quantum communication in aerial networks.;