Recently, I have started my capstone project with 3 other students, Brayden, Yuji, and Jacob. We started to dive into the topic “Leveraging AI for Improved Public Transit”, specifically looking at the Lane Transit District. With help from our sponsors, we’ve been able to start honing in on research for Lane.
We have had a little bit of a rough start with actually making physical progress, but the first part is just data collection. Often people underestimate the amount of time needed to collect data from various sources. As of right now, we are aware of what programs we are using (ie. BigQuery and Malloy), but largely unfamiliar with the data as of right now.
Once we get the data from the Lane Transit District, we will be able to use Malloy to clean up the data. BigQuery will help us find actionable insights in our data, so we can inform LTD of our findings. We are also going to collect data from organizations like CAHOOTS, which is an emergency service that will have good data for dangerous riding situations or weather data we might need.
Overall, the structure of the capstone course we are in is not to our benefit. We haven’t physically been able to do a lot. Even though we’ve done a lot of thorough research, we haven’t had actual data to work with. This week we are working with mock data to be able to have optimal strategies to find as many insights as we can from the actual data we’re going to get.
