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Studies where participants interact with their environment are necessary, for example to investigate pedestrian behaviour, in urban planning or for environmental studies. Existing methods such as field studies or 3D virtual reality environments frequently require a lot of effort to create realistic 3D worlds or are subject to real-world interferences. In this paper we propose an alternative approach that uses an immersive video environment (IVE) and a dynamic scene generator (DSG).We use overlays to dynamically generate video scenes to facilitate studying specific combinations of environmental factors with participants. We report on an initial case study in the context of studying pedestrian behaviour, where we show how the approach can facilitate studying how crowds and pedestrian signage affect route choices. Our approach can help researchers studying human-environment interactions in the lab.

Due to anthropogenic impact, more and more species are currently threatened. In order to detect this biodiversity loss, continuous and spatially distributed data of the fauna and further phenomena is needed. To gather such data, we have developed a Multi-Sensor-Feeder, which can be built up by every citizen. With a camera and a weight sensor, the feeder detects visiting animals, especially birds, and analyzes the species through AI. Further the feeder is equipped with different sensors like a thermometer, to gather complementary environmental data. The feeder is affordable and easy to reproduce by following a free manual, so that all citizens can explore the biodiversity at their place. Collected data is automatically analyzed and openly published in real-time and thus inspectable and downloadable for both researchers and citizens. With the poster, we suggest a way, how citizens can make an essential contribution to solve one of the world's current challenges.