Joined the team
EMF Walks in Brugg
An energetic tour to rediscover the town
We walked around the town of Brugg with a Software-Defined radio receiver and antenna, running open source software on a laptop to capture electromagnetic field emissions - observing the interplay of radio frequencies invisible to the eye or ear. We then produced a short music video with the result. Call it data art, if you like - we had fun making this together!
🎶 Credits 🎶
- Music by Static In Verona - Etcetera Ra Ra (© 2021 Gin Rubby Music)
- Penguin illustration by George Shaw (CC BY 4.0)
- Maps and open data from swisstopo and SFOE
- Data visualization made with Gqrx running on Fedora Linux
- Radio signals measured with an RTL-SDR V3 receiver
- Video recorded with Open Broadcaster Software and produced with Pitivi
📡 Why? 📡
The town hosting our event has a turbulent industrial past and many energy-related infrastructure and historic sites, most of it well hidden behind the façades of residence and commerce. Noticing sensors, transformers, mobile phone antennas, and other sources of radio interference, we were also much more aware of the technology that surrounds us even within a short radius. Our aim is to passively observe the variety and mystery of the patterns that we encounter during our walk. With a bit of practice, we find interesting frequencies, and learn to localize sources of interference. We may start to "see" the city through a new lens, even though in our case it is just a 1-dimensional waterfall-like visualization called a Spectrogram.
What's next 🧑🏼🏫
We planned our walk using swisstopo open data shown on the GeoAdmin map shown below. Based on these locations of interesting sites, we are creating an Actionbound quest to visit the most interesting industrial sites around Brugg. We can recommend frequencies to tune into, such the ones typically emitted by public works. In the future we could offer these "high tech" tours of the smart city to school classes or tourists.
🙇 Inspired by ⚡
Playing games where people interact and observe their impacts for data-driven modeling of occupant behavior
We walked around and found beautiful data just floating in the September air.
Joined the team