Setting Up Raspberry Pi To Run Bots

Server-web

Where’s the server? It’s under the table next to the couch!

The Raspberry Pi can be used for lots of cool projects, but because it’s cheap, small, and consumes far less power than a regular laptop or desktop, it’s perfect for applications where a computer needs to be running constantly, such as a server for running Twitter bots!

I have seven bots running at the moment, tweeting things like art assignments, “would you rather?” questions, and links from a 1995 “internet directory” book. Most of them post once an hour at varying times during the hour, meaning I need to run them from a computer that is always on, 24/7. I had previously used a Mac Mini, but it felt wasteful to have such a powerful computer that consumed so much energy, just to post 140 characters to Twitter.

By way of comparison, here is the energy use of a 2012 Mac Mini and a Raspberry Pi Model B:

 
RASPBERRY PI (MODEL B)
MAC MINI (2012)
IDLE2.19W11W
MAX2.64W85W

The Mac Mini also creates a lot of heat, even when not really doing anything. It’s average heat dissipation is 126 BTUs per hour, or the equivalent of 1/3 of a human!

Update: this post suggests that turning off video output (via RCA/HDMI) can save power consumption even more, especially for battery operation. Turn it off using the following command: /opt/vc/bin/tvservice -off, though it may not work on your device.

That’s enough convincing: let’s run some bots!

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Computers I’ve Owned

While working on a piece, I made a list of every computer I’ve owned or used regularly. I thought that we be 5-6, but the list kept growing and is not at 18.

YEAR
MAKE/MODEL
NOTES
1988-96Apple IIGSUsed in elementary and middle school, mostly to play Number Munchers and Oregon Trail
1994-96486 of some kindUsed at home for DOS games (didn't really know how to do anything else)
1996-98Compaq Presario 5140Used at home, used for games, going on AOL, graphics programs - all with that distinctive power/sleep button
1998-2000Some kind of eMachines desktopUsed at home for games, going on the real internet, using a cracked version of Corel Draw that Steve gave me, building webistes using hand-written HTML and launching on Tripod
2000-2004Apple Power Macintosh G3 (Blue & White)Used at college (I'm pretty sure this is the kind we had), used mostly for Photoshop, Illustrator, and writing papers
2002-2004Toshiba Tecra 8000 laptopUsed while in college (passed down from my dad's office), recorded some crappy little songs using the built-in sound recording app and a plastic mic
2004-2006Gateway laptop (still unidentified)Also used in late college and in early grad school, used for recording music on a cracked version of Cakewalk, making art using cracked versions of all kinds of software
2006-2009Mac PowerBook 12" laptopUsed during grad school and after for EVERYTHING, mostly on cracked software, too :)
2009-11iPhone 3GSMy first smartphone, bought after I lost the charger to my crappy cellphone, played lots of Scrabble on this
2009-13MacBook Pro 15" (2x)Used at first teaching job with NO cracked software! (2 different computers of the same model)
2011-13iPhone 4Replaced my previous smartphone, donated the old one to Angeles, played lots of Angry Birds on this
2012-presentRaspberry Pi Model BBought very early on, now runs all my bots
2013-preseNexus 10 tabletBought using a grant, mostly to run Processing sketches
2013-presentMacBook Pro 15" w Retina DisplayCurrent workhorse
2014-presentMac MiniAlso bought using a grant, mostly for installations (and formerly for and running bots)
2014-presentiPhone 5sCurrent smartphone, mostly use for email and directions/maps

* A note: by computer I mean anything that can do significant processing, like a smartphone, not anything that does computation or runs programs. I’m also excluding computers that I’ve used but don’t work here, like supercomputers :)

 

Recognizing The iPhone

Success

I’m spending the month of July in Utrecht, Netherlands as artist-in-residence at Impakt, working on a project to let computers recognize other computers. For early testing, I’ve trained a computer vision “cascade file” (above) for recognizing front-facing iPhones.

The resulting cascade files, like above, will be released as a printed book, as well as on GitHub.