Your smartphone is an amazing piece of technology, but it would be nothing without a cellular network which gives you the ability to text, talk, and browse the web. You may not see most of the massive infrastructure used by your cellphone provider, but it’s there. What If You Could See Your Cellular Network?
What the World Would Look Like If You Could See Cell Phone Signals and What If You Could See Your Cellular Network? articles have amazing visualizations of cell phone network signals. There are thousands of invisible signals bouncing around us all the time, and the world would be a very different place if we could see them. Data visualization artist Nickolay Lamm created psychedelic images of the cellphone signals that live in the air, but are invisible to us. I really recommend you to take a look at them and be amazed.
There are also many other radio signals than cell phone network. Check also What If You Could See WiFi? and What the World Would Look Like If You Could Actually See Wi-Fi Signals.
4 Comments
Teukka says:
Your RSS feed seems to insert newlines at the start – meaning it breaks a number of browsers which want the <?xml tag at the very beginning of a file.
tomi says:
Thank you for your feedback.
I will try to check that issue when I do some other updates on the site.
Tomi Engdahl says:
One apartment’s Wi-Fi dead zones, mapped with a physics equation
A doctoral student does the math on where his Wi-Fi is, and isn’t.
http://arstechnica.com/gadgets/2014/08/mapping-wi-fi-dead-zones-with-physics-and-gifs/
A home’s Wi-Fi dead zones are, to most of us, a problem solved with guesswork. Your laptop streams just fine in this corner of the bedroom, but not the adjacent one; this arm of the couch is great for uploading photos, but not the other one. You avoid these places, and where the Wi-Fi works becomes a factor in the wear patterns of your home. In an effort to better understand, and possibly eradicate, his Wi-Fi dead zones, one man took the hard way: he solved the Helmholtz equation.
The Helmholtz equation models “the propagation of electronic waves” that involves using a sparse matrix to help minimize the amount of calculation a computer has to do in order to figure out the paths and interferences of waves, in this case from a Wi-Fi router.
Cole writes that making the mapping simulation a Web service would probably be unfeasible due to the intensive calculations
Tomi Engdahl says:
This ESP32 Antenna Array Can See WiFi
https://www.youtube.com/watch?v=sXwDrcd1t-E
More information is available on the project website of the ESP32 antenna array “ESPARGOS”: https://espargos.net/
Source code for Python library + demos: https://github.com/ESPARGOS/pyespargos (directory “demos/camera” for “WiFi camera” demo)
As a research assistant at the Institute of Telecommunications at the University of Stuttgart, I work on multi-antenna systems like (distributed) massive MIMO, with a focus on wireless channel measurement platforms and algorithms for processing channel measurements (classical and deep learning-based).
One day, my (incredibly talented) colleague Marc Gauger suggested to use ultra low-cost ESP32 chips instead of software defined radios for channel measurements. I was highly sceptical at first, but when he showed me a minimalistic prototype he had soldered together, I was intrigued by the idea of being able to demonstrate my algorithms in real time using WiFi signals. In a series of Bachelor’s / Research theses, my excellent students Tim Schneider, David Engelbrecht and David Kellner helped me develop the ESP32 antenna array “ESPARGOS”.
Measured CSI dataset used for AoA / TDoA visualization: https://espargos.net/datasets/data/es…
AoA / TDoA localization source code (needs some minor modifications to be applied to espargos-0005 dataset): https://github.com/Jeija/ToA-AoA-Augm…
Channel Charting source code for the animation in the video: https://github.com/Jeija/Geodesic-Unc…
Tutorial on Channel Charting: https://dichasus.inue.uni-stuttgart.d…
My research on (distributed) massive MIMO, Channel Charting and other algorithms for multi-antenna systems is funded by the German Federal Ministry of Education and Research (BMBF) within the project Open6GHub (grant no. 16KISK019).
I also want to express my gratitude towards ARENA2036, who hosted our measurement campaign for Channel Charting, and to my colleague and Channel Charting expert Phillip Stephan, with whom I co-authored several papers on Channel Charting and who assisted me with the creation of this video.