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The growing trend to use mobile devices and applications to collect data relating to fitness activities has resulted in large amounts of sensor data being generated. Further, in some cases the fitness data is shared over social networks. This collected data has potential uses in a number of fields including: public health and population health data, urban planning, fitness trends analysis, social network analysis and personalization of health information. As the motivation for creating this sensor data already exists for the individual in relation to fitness benefits and health monitoring, this type of participatory sensing approach has a lower barrier to entry. However, there is currently no structured approach to collect and re-use this sensor data. This paper describes the distinct types of fitness sensor applications; conceptual architecture for data collection and aggregation and the steps and developments that would improve the quality and usability of data collected. Further, the types of secondary uses for smart cities of this collected data are explored.
Clarke et al. (Thu,) studied this question.