HotCity: enhancing ubiquitous maps with social context heatmaps

In this paper we present HotCity, a service that demonstrates how collecting and mining the interactions that users make with the urban environment through social networks, can help tourists better plan activities, through sharing the collectively generated social context of a smart, connected city, as a background layer to mapped POI. The data for our service stems from the collection and analysis of 1-month worth of collected human-physical environment interactions (i.e., Foursquare check-ins) data for Oulu, a medium-sized city in Finland, where our service is deployed in ubiquitous public displays. Our analysis demonstrates that a good model of the city's dynamics can be built despite the low popularity of Foursquare amongst locals. Our findings from the field-based trial of the HotCity service yield several useful insights and important contributions. We found that the method of using a heatmap as an intermediate layer of environmental context does not negatively affect the experience of users at the cognitive level, compared with a more traditional map and POI type of interface, where temporal aspects of context are not present. In the concluding sections, we discuss how this cloud-based service can also be used in a variety of ubiquitous computing platforms.