(Week 6) Uncertain Certainties? Certainly.

This week was a blizzard of bug fixing and board games. Us CS folks really got into the latter this week, especially a popular one called “Catan.” Basically, there’s this island on which we place settlements, roads, and cities using resources that we’ve mined from specific tiles, which, in a cool kind of twist, are all hexagonally-shaped. I promise, it’s way more fun than I’m making it sound.

Progress Report

I believe I’ve successfully implemented location services in addition to my sensor samplers. I’ve also altered the sampling rate so it runs for fifteen seconds every minute instead of five. During this time, location data gets stored into the app’s database if it’s changed at least one meter over a second and the motion sensors store all changes in movement. I managed to hack my way around the asynchronous troubles I was having last week, so now my database closes at the right time at the conclusion of each fifteen-second blurp and I don’t get stuck in an infinite loop, waiting for the right condition.

Keeping the ball rolling, I also set up the framework to output CSV files that contain the information from my app’s database. At the very least, I know the code reacts the right way when there’s no SD card in the device. Unfortunately, I haven’t had the chance to test it with an SD card yet, since I was having trouble fitting it into the tray earlier today when the department magnanimously provided me with one. The card was oddly-shaped, with a sort of toothy terrain along the long edges, and I had a hard time even trying to fit it into the regular-sized SD card adapter that it came with.

In addition, I started learning this week about some of the clustering algorithms that exist in the world. I don’t know a whole lot about the mechanics yet, but from what I understand so far, data gets grouped together when it shares some common property with other data from the same set. The more similar the data is to the rest of the group with respect to the common property, the closer to the center of that group it gets classified. Think of it like looking at pom-poms that are sitting on a table, where each pom-pom is a cluster of data points that are related in some way.

So that’s pretty much what I’ve been up to this past week. As always, stay thirsty, my friends.. for knowledge..

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