Coming from another huge college, we know how hard it can get to find a study space (especially during the exam season). According to numerous studies, the amount of time invested in quality studying is directly proportional to knowledge absorbed and exam grades, so we thought that it'd be great if we could come up with something that helps maximize the time students can spend with their study material rather than library hopping.

What it does

Compass currently takes in years' worth of OSIsoft data collected from the 134 buildings at the UC Davis campus and analyzes it for Electricity usage in real time and compares it to trends over the past to recommend the perfect study place.

How we built it

We build Compass with a lot of attention to detail. Because the OSIsoft data is extremely high resolution (a new reading is taken after every 5 seconds with some sensors!) we had to come up with an extremely smart and fast algorithm that prevents overloading local memory and the server at the same time. Most of our code is written in Python with JSON from the OSIsoft PI Web API being parsed right in the code for manipulation.

Challenges we ran into

The OSIsoft databases are extremely detailed and huge. Moreover, the API was meticulously designed to be powerful which demanded an absurd amount of time to be completely understood. We had to understand how the API worked at its very core to really value its power and optimize it. Because Compass is designed to be operating in real-time we had to decide on what information to keep on the app and what to request from the server so we could deliver the fastest results. Furthermore, because we extracted data from different sub-databases within, we realized that some of the data we were getting was inconsistent with the previous data, so we had to reconcile those differences in sequences by hacking our way through URLs and clever implementation of Python code.

Accomplishments that we're proud of

We are really proud that we were able to get familiar with the API in very little time thanks to the OSIsoft Web Developers and the amazing HackDavis Mentors. The time we saved was key to being able to finish the project in time. We are also happy about being able to meet our runtime expectations with a whole lot of trial and error in an effort to keep our app light and minimizing calls to the server.

What we learned

We learned the importance of having amazing mentors to guide through the process. It's eye-opening to learn how great guidance help in the realization of initially daunting projects. Moreover, we learned how to take things one at a time so as to not overload and overwhelm ourselves with the thought of what is to come.

What's next for Compass

Compass can have advantages beyond the UC Davis campus, if other colleges too make their usage data etc. public. Moreover, it can have an impact outside of college campuses if we use emission data from a variety of motor vehicles to determine the optimum pooling routes using the same algorithm.

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