BoilerBites

BoilerBites: Fuel your day, pair meals to your needs! Discover the best food courts for your dietary desires, saving you time and hassle of doing it yourself!

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Inspiration

  • We wanted to address the lack of variety within the food court and the inconvenience of finding foods that fit everyone's needs. Our own groupmate Arushi is a vegetarian, and it's oftentimes a burden to look through every single dining court and check which one has the most vegetarian foods for the time. We wanted to make life easier, so we came up with Boiler Bites!
  • We wanted to find a way to save people time and effort put into searching for dining courts.

What it does

  • The app allows the user to enter their dietary preference, such as Vegetarian foods, and the app gives them a list of dining courts serving the most items fitting their needs. Within these courts, they can also look into the available food options, which have already been sorted from the most nutrient-dense foods to the least (all of which are foods that fit their dietary needs).
  • This saves users the task of researching Purdue Dining to find which court has the most options.

How we built it

  • We utilized Flutter to develop an app on iOS called "BoilerBites," utilizing data from the Purdue Dining Court website and importing that data into Microsoft Excel, which was what we used to devise the personalized meal plan for the user.
  • Used a language named Dart to program most of the app.

Challenges we ran into

  • We were unable to scrape the information on the Purdue Dining Court, as we tried using R, Python, BeautifulSoup, and Selenium, but with no success. We think the data may have been inaccessible to the public because we were unable to export the HTML files or access them outside. The same scraping functions worked on other websites.
  • Loading the Excel data into the mobile application resulted in many errors, as we were unable to have the data displayed within the app.
  • There were also many issues in the flutter code, as it was difficult to divide the data from the Excel sheet and make sure the indexes matched up properly.
  • There were also many errors within the code where the text would overload the columns, resulting in the page being overloaded.

Accomplishments that we're proud of

  • Being able to import the data from the Microsoft Excel sheet into the Dart code and turning it into a 2-D Array.
  • Building an app that can sort through a lot of data based on user inputs.
  • Developing an app that has practical purposes within the campus.

What we learned

  • We learned multiple ways to web-scrape using R, Python, BeautifulSoup, and Selenium.
  • Learned how to integrate .txt files into apps.
  • Learned to debug/code in Flutter using Dart
  • Learned how to create Excel Sheets that housed and applied formulas to large amounts of data

What's next for "BoilerBites"

  • Partner with Purdue Dining to integrate all the information into one app, and also integrate Google Maps so it guides users to the nearest dining court. We can eventually try to come up with an algorithm that can learn the user’s preferences, checking if they value distance to dining courts over food options. We can then provide new rankings.
  • We also want to make a "diet plan" where the user can input their personal dietary preferences such as caloric intake and the number of meals they eat per day, and have the app recommend them a balanced meal. Ex. If the person has a daily caloric intake of 2,500 calories, the app can recommend a 3-meal plan, where the app recommends which items to eat for breakfast, lunch, and dinner so that the user can reach their caloric needs.
  • We can start integrating retail and non-dining court locations. We need to compel every seller on campus to provide online the nutritional information necessary for students.
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