Urban Environmental Sensing with Drones
Data Visualization & Video
ArcGIS, Grasshopper ELK,Human, Horster, Firfly, 3D Ptint, Drones, Sensors
The project is aim to gather urban data of CO2, PM 2.5, O3, sound, humidity and temperature by using sensors DHT 22, K-O3 etc., and visualizing them into a video to alter people’s perceptions on urban construction. We utilized the campus of the Tongji University as the case study of our investigations, and operated drones and bicycles equipped with sensors and cameras to document the environment.
With this video, we wanted to explore the story of two students with similar interests but different backgrounds. Both are trying to discover their environment and make sense of different parameters.
Sensors that map urban micro-climates or micro-environments are typically fixed to a building, or traveling with a researcher who is either walking or biking through an environment. While bicycles outfitted with sensors were used for this project, the drones allowed Bogosian and her collaborators to collect vertical data from buildings and tall vegetation. Using photogrammetry, the drones were also used to create a 3D scan of the university. These 3D visuals were then fed into the Microsoft's HoloLens augmented reality headset worn by the film's female character, as a way of visualizing how she might learn about her environment.
We're interested in how knowing more about your immediate environment can help you make better decisions in terms of the design of buildings. But, ultimately we're fascinated with different visualization methods that can basically allow you to see these individual parameters like air quality.
While the woman maps temperature, humidity, CO, CO2, nitrogen dioxide, ozone, and particle matter, the man maps surface temperature, surface types, and environmental textures. The two never interact, but continue on their own personal scientific journeys, together building a more complete picture of the Tongji micro-environment.
The drone's vertical gradient allows us to better understand how specific type of buildings and environments repel or trap air pollution. To do this, they used drone swarms outfitted with Arduinos and various sensors to make the data collection as spatial and temporal as possible.
Environmental 3-D printed box
Electronic Speed Controller
Environmental Sensing Kit
The film is an exercise in in storytelling through data. It was important for them to think of how they could communicate this data to an average person, but also develop a spatio-temporal visualization technique that even a scientist could find useful.
The amount of spatio-temporal resolution you get from drones is unlike anything else we could achieve. It's easier and cheaper to give people the sensors to do the data collection, but with drones we can program them to have a certain speed and be more consistent. So, spatio-temporal mapping is often complimentary to the field work of mapping we would be doing either by walking or using bicycles.
Sensor - the other
Digital Architecture Design