Immaterials: Light painting WiFi


The city is filled with an invisible landscape of networks that is becoming an interwoven part of daily life. WiFi networks and increasingly sophisticated mobile phones are starting to influence how urban environments are experienced and understood. We want to explore and reveal what the immaterial terrain of WiFi looks like and how it relates to the city.

In order to study the spatial and material qualities of wireless networks, we built a WiFi measuring rod that visualises WiFi signal strength as a bar of lights. When moved through space the rod displays changes in the WiFi signal. Long-exposure photographs of the moving rod reveal cross sections of a network’s signal strength.

The measuring rod is inspired by the poles land surveyors use to map and describe the physical landscape. Similarly, our equipment allows us to reveal and represent topographies of wireless networks. The measuring rod uses a typical mobile WiFi antenna to measure reception, and draw out 4 metre tall graphs of light.

This generates what William Mitchell called an ‘electromagnetic terrain’ that is both intricate and invisible, and only hinted at by the presence of antennas (2004, p.55)

The size of the measuring rod and the light paintings it creates emphasises the architectural scale at which WiFi operates, and situates the networks in the physical environments that they are a part of. The light of the measuring rod pulses as it is being moved, which creates dashed lines rather than solid ones. This creates a semi-transparent texture that allows the visualisation to appear within the physical setting without covering it

Our expeditions around Grünerløkka, and the time-consuming work of measuring networks by walking with a 4 metre tall instrument gave us a sense of the relationships between WiFi networks and the physical environment. Architectural forms, building materials and the urban landscape shape how networks spread into the city, and can make WiFi seem spatially unpredictable. The light paintings show how the network’s behaviour depends on where it is located and how the city around it is built.

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