TUNED aims to develop an integrated toolkit to assess noise, societal and ecological impacts of new aviation entrants in U-space, supporting their sustainable deployment and the development of policy guidance. Focusing on uncrewed aircraft systems, it addresses the limitations of existing drone noise models, which rarely capture diverse vehicle types, operating conditions, or wider societal and ecological effects.

The project will develop a machine-learning-powered toolkit that models acoustic impacts across urban, peri-urban and rural environments, and links noise exposure to human perception and wildlife disturbance. Based on representative case studies, it delivers advanced sound source modelling, noise acceptance thresholds under different operating scenarios, and methods to assess impacts on wildlife. The toolkit enables users to input operational trajectory data and receive estimated human and ecological noise exposure, supporting evidence-based U-space decision-making.