MC2 - Mining Factory Pollution Data through a Spatial-Nonspatial Flow Approach

EVL Project Team (from left to right): Andrew Burks, Joe Borowicz, Elisabeta Marai (faculty advisor), Joshua Castor and Manu Thomas - photo courtesy L. Long, EVL

Authors: Castor, J., Borowicz, J., Burks, A., Thomas, M., Luciani, T., Marai, G.E.

Publication: IEEE Visual Analytics Science and Technology (VAST) Challenge 2017 Proceedings, Phoenix, AZ, pp. 1-2

Mini Challenge 2 of the VAST Challenge 2017 focused on a small industrial area south of the fictional Mistford preserve, specifically around four manufacturing factories. Our main goal was to develop a visual analytics tool to explore the spatio-temporal chemical readings and wind data. Specifically, we wanted to determine which factories were responsible for emitting which chemicals and to determine the performance of the nine sensors in the area. In order to help achieve this goal, we developed a web-based application that utilizes interactive visualizations and path line analysis for revealing sensor errors and chemical reading spikes, along with pinpointing the possible sources of chemical reading spikes.

Date: October 1, 2017 - October 6, 2017

Document: View PDF

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