Visual Analysis of Multivariate Time Series of Static and Mobile Sensors

The mini-challenge 2 of VAST Challenge 2019 asks the participants to make sense of the radiation conditions in St. Himark using radiation readings from the both stationary monitors and mobile sensors, particularly, to detect and monitor a bunch of contaminated cars running in the city. This paper presents our visual analysis solution to detect and localize these cars using various visualization techniques, including small multiples, distribution histogram, and animation. As a result, we detected most of these cars, characterize their behavior during the given time period and give suspected locations of these cars at the end. We also developed a visual analysis interface using Tableau to help users evaluate the uncertainty of sensor readings, make sense of radiation changes in different area, and make future plans to deploy more sensors.