In this paper, we present a real-world study where a community-based tracking infrastructure has been put to good use for understanding human mobility during the COVID-19 outbreak, in order to predict/contrast its diffusion. In particular, the infrastructure, deployed in the Madeira Archipelago (Portugal), is able to collect a massive amount of spatio-temporal data, that can be enriched with potentially independent data sources of additional values (such as the official number of people affected by the coronavirus disease). These enriched hyper-local data can be exploited to visualize the correlation between COVID-19 diffusion and the mobility of people. We here present the deployed infrastructure and the data visualization, interactive system to make sense to human mobility data during the COVID-19 outbreak.