Activity recognition in outdoor sports environments: Smart data for end-users involving mobile pervasive augmented reality systems

Abstract

Activity recognition is an increasingly relevant topic in the context of the most varied outdoor end-user services. In outdoor environments, activity recognition based on close-to-real-time information is key in providing awareness to the user about their habits and thus to allow the user to better perform. Such promptness is today provided via multiple sensors and performed both actively and passively via fitness gadgets, smartphones, mobile pervasive systems, and other personal mobile gadgets. In this context, it is relevant to understand how data from multiple sensors can be fused, interpreted and classified, to best provide feedback using the recognized activities, especially for smart data feedback. This paper provides a first analysis in activity recognition and adapted informational feedback to the user based on data fused from common sensors which are today available in personal devices is presented, focusing existent restrictions imposed by applications' usage in outdoor environments.