Activity recognition approaches for smart cities: The City4Age use case

Abstract

Activity Recognition is an important ingredient that allows the interpretation of elementary data. Understanding which activity is going on allows framing an elementary action (e.g. “a movement”) in a proper context. This paper presents an activity recognition system designed to work in urban scenarios, which impose several restrictions: the unfeasibility of having enough annotated datasets, the heterogeneous sensor infrastructures and the presence of very different individuals. The main idea of our system is to combine knowledge- and data-driven techniques, to build a hybrid and scalable activity recognition system for smart cities.