The growing average age of the urban population, with an increasing number of 65+ years old citizens, is calling for the cities to provide global services specifically geared to elderly people. In this context, collecting data from the elderly’s environment and his/her habits and making them available in a structured way to third parties for analysis, is the first step towards the realization of innovative user-centric services. This paper is focused on a performance analysis of three main blocks of an IoT-aware monitoring system: (i) data capturing in home and in the city, (ii) data store and management in the Cloud and, (iii) data analytics. Critical points in the system architecture have been highlighted trying also to define potential solutions able to overcome them. The analyzed system architecture is used by the H2020 City4Age project to help geriatricians in identifying the onset of Mild Cognitive Impairment (MCI) and frailty conditions.
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