Barmpounakis, ManosEspadaler-Clapés, JassoTsitsokas, DimitriosMordan, TaylorGeroliminis, Nikolas2025-09-192025-09-192025-09-182025-09-1110.3390/drones9090637https://infoscience.epfl.ch/handle/20.500.14299/254156European cities are increasingly turning to data-driven solutions to tackle the complex challenges of urban mobility, yet many still lack high-resolution, multimodal data to make fact-based interventions. This paper presents the aims and initial findings of large-scale drone-based experiments conducted across five European cities—Athens, Madrid, Mykonos, Limassol, and Helsinki. Designed in close collaboration with local stakeholders, each deployment targeted city-specific objectives ranging from traffic congestion and safety to changing multimodal behaviour. Using GDPR-compliant computer vision techniques, we extracted privacy-preserving trajectory data that reveal detailed insights into flow dynamics, modal interactions, and behavioural patterns. Around 1.5 million trajectories were extracted in total. This paper offers a comparative analysis of findings across contexts and key lessons around stakeholder engagement, operational scalability, and ethical data practices. Our results demonstrate the potential of drone-based mobility monitoring as a powerful, flexible tool for supporting sustainable and inclusive urban transport planning across Europe.entext::journal::journal article::research article