There was a lot done since the last blog post. The biggest change was changing how the detection works. Before, I planned on having the app fire a notification at night hours the moment the user's distance from one of their home locations exceeded a certain customizable threshold. However, a better way of doing things is to send the notification the instant the user enters their home location at night hours. This is better because the notification would then fire (ideally, sans GPS inaccuracies) as soon as they leave their car and are walking to their house. In addition, the app now plays a sound and vibrates upon notification, so the user would be reminded pretty aggressively.
I plan on publishing the Android version before moving on to the iOS version. In retrospect this would take a little more work than anticipated, due to the complexity of publishing. In addition, I plan to make a "help" website that gives details on how to use the app, as the way the app works, by nature, is not too intuitive.
SUCCESS! I got selenium running with a little bit of code. It basically takes over a browser window and allows you to give the browser input through python code. We will soon be able to scroll to the bottom of a friends page and load the html of said page to get the id's of someone's friends. I will implement it in our project tomorrow, but we are back on track to collect data and I am happy.
After some setbacks and a long search we found the best SDK for our app. Vuforia is a cross platform SDK that has the necessary computer vision-based image recognition needed for our app. Vuforia offers two options for developing, you can either write a single native app or use a Unity base package. Both methods would allow you to reach the most users across the widest range of smartphones and tablets but unity has the built in rendering engine.