In this workshop held by the MIT Senseable City Lab, in collaboration with the Austrian Institute of Technology, participants experimented with changing public spaces with the help of image processing, environmental sensors, and social media analysis. The workshop provided an introduction to theories and models of how people move, talk and interact in public space, and how this information can lead to a better design for public spaces.
The first half of the workshop took place in a public space near the pavilion; participants had the opportunity to transform the space using a variety of objects and marking tools. Cameras and mobile sensors captured the activity as it happened, while servers collected social media traces in real-time.
Afterward, we returned to the pavilion to analyze the information collected in the space. We demonstrated how image processing can detect pedestrian paths, behaviors, and group dynamics automatically. We also visualized the noise, pollutant, and social media data, shown in the graphs below, and invited participants to interpret these results.