City Scanner

Data visualization for a mobile urban sensing platform

City Scanner deploys various types of environmental sensors on garbage trucks in the City of Cambridge, Massachusetts. The project proposes a drive-by solution to capture the spatiotemporal variation in environmental indicators in urban areas, such as air quality or the thermal flux of the built environment. These datasets play a significant role in smart cities by empowering advanced analytics solutions for decision makers and urban managers.

In this project at MIT SENSEable City Lab, I collaborated with researchers to identify research questions and aggregate data in an actionable way. My main role was the concept, design, and development of an interactive data visualization that allows to explore raw sensor data as it is collected. I also contributed to the thermal image processing, data infrastructure, and sensor deployments.

Head over to the project website for more information or launch the application.

The interface consists mainly of a map, data timeline (bottom left) and histogram/detail window (bottom right).

The visualization contains 1.6 million data points — including thermal images, temperature, humidity, and air quality data — that can be viewed and filtered over space and time. The web application also contains on-the-fly rendering of thermal camera videos. See the video at the top of the page for a walkthrough.


Project Host: City Scanner is a project by MIT SENSEable City Lab
Team: Carlo Ratti (Director), Amin Anjomshoaa (Project Lead), Fábio Duarte (Project Manager), Thomas Matarazzo (Post-doctoral Researcher), Priyanka deSouza (Air Quality Analyst), Rex Britter (Research Adviser), Daan Rennings (Data Analyst), Philipp Schmitt (Web, Visualization), Lenna Johnsen (Designer), Louis Charron (Designer), Lylla Younes (Web)
Visualization/Concept/Web: Philipp Schmitt
Developed with: Mapbox GL, D3.js, turf.js, chroma.js, MySQL