Kunchala Anil

Title: Privacy-preserving Pedestrian Movement Analysis in Complex Public Spaces

Supervision Team: Bianca Schoen-Phelan, TU Dublin / Mélanie Bouroche, TCD

Smart cities should encourage the use of walking as it is one of the most sustainable and healthiest modes of transport. However, designing public spaces to be inviting to pedestrians is an unresolved challenge due to the wide range of possible routes and complex dynamics of crowds. New technologies such as Internet of Things (IoT), video analysis, and infrared sensing provide an unprecedented opportunity to analyse pedestrian movements in much greater detail. Any data captured for analysis must also protect the privacy of pedestrians to avoid identification via direct imagining or movement patterns. This project pushes the state-of-the-art pedestrian movement analysis by proposing the use of 3D multi-modal data from outdoor locations for quantitative wireframe representations of individuals as well as groups, which involves crowd movement simulation, IOT data capture, privacy-preserving data analytics, the smart city paradigm and health and wellness.