Abstract

Rapid urbanization presents multifaceted challenges to urban mobility, necessitating innovative solutions for environmental and social well-being. Despite extensive research, identifying critical urban hotspots and proposing effective interventions remain active research areas. This paper presents a knowledge engineering framework leveraging urban data repositories to identify key infrastructure points and promote sustainable, accessible mobility. Utilizing advanced data science techniques, the study focuses on factors influencing pedestrian and cyclist movements, aiming to foster active transportation and improve citizens' health. Through a case study in Barcelona, the paper demonstrates the efficacy of the approach while maintaining generalizability. The data-driven analysis explores variations in accessibility and mobility, addressing affordability issues and barriers in emerging micro-mobility solutions. These insights contribute to informed decision-making and policy formulation, facilitating global transitions towards sustainable urban futures.