Crime Owl

Inspiration

At one point or another, every individual picks up their bags and decides to explore a completely new destination which can become their home for the next couple days or even years. This could be a student going to live in college, a graduate relocating to a new area closer to their work, or a family looking to stay at a resort for their vacation. Moving or staying at a new location is a crucial step in anyone’s life, often requiring intensive planning and endless battles with yourself as you fight the mixed jitters of nervousness and excitement to start a new chapter in life. Although, just as it is important to be open to new beginnings in one’s future, it is just as important to make sure to be safe at all times. As students who have all left the comfort of our home to start college, we have faced these issues ourselves and applied our passion of giving back to our community to provide a viable solution to public safety. We work to provide users with invaluable resources that display raw details of crime patterns in specific locations to enlighten potential movers and promote safer communities. In our project, we decided to focus on the College Park area and aim to educate users about the incidents local to them.

What it does

Our project compiles data reported by the UMPD and displays it as user-friendly graphs and statistics. Our UI is simple to use and contains graphs about top 10 incidents in the area, for example.

How we built it

We began by webscraping the UMPD incident site with Beautiful Soup, making sure to collect information from every month from 2016 to 2023. We then applied data science principles to clean our data and present the data visually. We simultaneously built a web application using Python, Flask, HTML, and CSS to be able to present the data to our users. We also created a unique logo and website background in Canva.

Challenges we ran into

We ran into many issues with pushing and pulling our code into GitHub. At first, we all lacked coordination, and it hindered our progress. But as the day went by, we were able to coordinate and work properly as a team, we no longer had issues with it. We also had a couple issues with our time management. I believe if we had planned out a schedule for our work and set deadlines for ourselves beforehand, then time management would not have been an issue.

Accomplishments that we're proud of

We are proud that we were able to create a full dataset made of web-scraped information. We are also proud of our UI, and the amount of work we were able to complete within the hackathon time.

What we learned

We learned how to web scrape and build UI with Python's Flask. We also learned how to split up tasks and work effectively with the three of us.

What's next for Crime Owl

We hope to make the data visualizations interactive and incorporate real-time data that updates regularly. We also want to make the UI streamlined for both computer screens and phone screens.