Analysis and Visualizations

With our dataset, we aim to communicate beacon activity in public spaces within Manhattan and Brooklyn. Therefore, the data is analyzed to check for insights such as no. of unique UUIDs, top UUIDs detected, details on manufacturing companies, mapping of detected beacons, their physical addresses and potential retail stores identification etc.

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To communicate the findings visually, we used Google Maps JavaScript API which allows users to add features on geospatial maps along with zoom-in and zoom-out interactions with all stores and streets information display. We also built supportive interactive visualizations indicating the density of beacon signals detected in a particular region within Manhattan and Brooklyn utilizing D3.js, Plotly JS and Mapbox.  

Besides, we visualized standardized beacon distribution data in census-tract-level using tree diagram in Tableau, based on no. of beacon devices detected per minute.