Andy Molenda has blogged about his experiences using Grav which is a low-memory footprint and highly efficient flat-file CMS. It has enabled him to run a blog on his 256MB Pi with very good performance. He has written up how to install the stack necessary to run Grav – read it here.
Kiran Kankipati has posted to the Raspberry Pi Google+ community about TrafficSqueezer which is a WAN optimization device that runs on the Raspberry Pi 2. They’ve provided a downloadable OS image for easy set-up and it relies on using a USB-to-Ethernet adapter. Read more here.
Francois Dion is currently blogging about his team’s (Piedmont Triad of North Carolina) efforts to launch a high altitude balloon payload with 7 (count ’em!) networked Raspberry Pis and multiple cameras. Read more here.
I can’t pretend that I know exactly what Matt Williams is talking about in his article, but suffice to say he’s doing something very impressive with his Pi. I’ll let him explain:
Substructure substance matching is, in many ways, a non-trivial exercise in Cheminformatics. The amount of data used to determine matches grows very quickly. For instance, one method of describing a molecule’s “fingerprint” uses 880 bytes. Or 2^880 combinations. This space is very sparsely populated, but there are still many potential combinations.
If you’re still with me, in his article he explains how the Pi does pattern matching with grep and how it speeds up when reading from the cache. Read his article here.
This is simply beautiful. Poopi and Piter have created a “paludarium” – an enclosed biodome in which environmental conditions are simulated – which contains both land-based and water-based lifeforms.
The paludarium is controlled by a Raspberry Pi and 4 ATmega 168P chips and has the following equipment hooked up:
It really is a lovely project they’ve designed. I can’t find anything more about either the project or the guys (or girls!) behind it, but here’s a video of it in action from simulated sunrise to simulated sunset.
The music is “Healing” by Kevin MacLeod.
I spotted this over at the Central Florida Aquarium Society.
David has written a great little app that creates a web server on the Pi that is used to display graphed information about the Pi 2’s 4 CPUs. He has written up the project here and made the code available online. You run the script on the Pi and then open up a browser on another device to see the graphs. See a video of it in action below:
