Know-how Expertise in Intelligent Urban AI Systems

At Neapolis University Pafos, we offer specialised know-how in Machine Learning, Federated Learning, Explainable AI (XAI), task offloading, and mobility management—key enablers for next-generation urban intelligence.
Our research focuses on designing adaptive, secure, and resource-efficient AI systems that operate across edge–cloud infrastructures in real-time environments. This includes:

• Federated Learning to enable collaborative intelligence across silos (e.g., vehicles, sensors, UAVs) while preserving data privacy;

• XAI methods to ensure transparency and interpretability of decisions made by AI agents in safety-critical or user-facing applications;

• Task offloading and mobility-aware orchestration to dynamically distribute computational workloads based on network conditions, energy constraints, and mobility patterns.
  This expertise supports the goals of climate-neutral, resilient, and data-driven urban ecosystems, aligning with the broader vision of the DUT Transition Pathways.