When we first saw [Jeffrey Nelson]’s G1 based robot we immediately wondered what the transport for the controls was. The G1‘s hardware supports USB On-The-Go, but it’s not implemented in Android yet. It turns out he’s actually sending commands by using DTMF tones through the headphone adapter. The audio jack is connected to a DTMF decoder that sends signals to the bot’s Arduino. He wrote client/server code in Java to issue commands to the robot. You can find that code plus a simple schematic on his site. A video of the bot is embedded below.
Continue reading “Forknife, Android G1 Controlled Robot”
TEMPEST is the covername used by the NSA and other agencies to talk about emissions from computing machinery that can divulge what the equipment is processing. We’ve covered a few projects in the past that specifically intercept EM radiation. TEMPEST for Eliza can transmit via AM using a CRT monitor, and just last Fall a group showed how to monitor USB keyboards remotely. Through the Freedom of Information Act, an interesting article from 1972 has been released. TEMPEST: A Signal Problem (PDF link dead, try Internet Archive version) covers the early history of how this phenomenon was discovered. Uncovered by Bell Labs in WWII, it affected a piece of encryption gear they were supplying to the military. The plaintext could be read over that air and also by monitoring spikes on the powerlines. Their new, heavily shielded and line filtered version of the device was rejected by the military who simply told commanders to monitor a 100 feet around their post to prevent eavesdropping. It’s an interesting read and also covers acoustic monitoring. This is just the US history of TEMPEST though, but from the anecdotes it sounds like their enemies were not just keeping pace but were also better informed.
At first glance, this may look like a retro styled monome, but it is actually quite different. Merging a Project64 key pad and a Voice Shield for Arduino, [Spikenzie] has made a sound effects box. Each button triggers a unique sound that is stored in the Voice Shield. Of coarse, it will be like a game of memory trying to remember what sound is where. You can see a demo video here.