We research techniques for improving safety of pedestrians, traffic flow, and smart streetscape applications. We aim to accomplish precise localization and tracking of objects by utilizing infrastructure-installed multimodal sensors such as cameras and lidars to provide a global view of the behavior of smart city traffic participants. We rely significantly on traffic intersections which are particularly suitable locations for the deployment of computing, communications, and AI-based services for smart cities of the future. The abundance of data to be collected and processed, in combination with privacy and security concerns, motivates the use of machine learning and deep learning processing, and to deploy the edge-computing paradigm which aligns well with physical intersections in metropolises.
