aaasen

I'm building an expedition weather app that works via satellite messengers like Garmin inReach, ZOLEO, and iPhone satellite messaging.

It has been really interesting trying to fit a detailed weather forecast into about 1,000 bits. I'm using an rANS entropy coder fitted on historical weather forecasts. I'm able to fit about 100 time periods (~4 days of hourly data) into a 160 character message, using just a couple bits per variable on average.

Github: https://github.com/aaasen/goingblue Site: https://going.blue

This is awesome! Great way to visualize the data and I really like that you used IRC.

It only shows the 1000 most common locations. Sorry!

Thanks Leland!

I also used the same data in a 3D visualization with the Oculus Rift. You can check out a demo here: http://youtu.be/dgMOdzfoPgs?t=31s

Author here, sorry about the spikes where people do not actually live. A lot of users put only their country and not city, and I didn't want to throw that data away.

I probably should've checked the specificity of the location and only thrown out the data for large countries like Russia and China, or distributed it across all other data points in the country.

Interesting project if you want to fork it!

Thanks for the link, just watched it all the way through. I felt disturbed thousands of miles away - can't imagine what it's like to actually be there, so close to death and destruction every second of every day.

It's crazy that there are so many huge companies that I've never heard of. Instagram's acquisition was huge news at $1B, but I didn't hear a peep about Ariba at $4.3B or Genzyme at $20B.

It's easy to think that consumer oriented web startups are what's hot, but this data proves otherwise.