LifeLine was created for 3 main reasons. One being tiny labels. Tiny Labels can be an issue for many people because of deteriorating eyesight and no0t being familiar with the English language. We also wanted to create this because people are usually in a hurry when grocery shopping especially in these uncertain times. Reading the tiny food labels and reading all of them can be a very tedious task and it can be very hard to do this if someone has a lot of allergies or dietary restrictions. We also want to help those who are new to English and aren't able to understand every ingredient or be able to spot them due to their unfamiliarity with the language.
What it does
LifeLine is an innovative android app that checks if users are allergic to certain foods. Users will input what dietary restrictions they have or what allergies they have and when they take a picture of the labels or ingredients of the food our machine learning software and firebase will check to see if you can or cannot eat the food.
How I built it
Lifeline uses a plethora of technologies. The backend end of our application was written with Kotlin and java. And where the magic happens is when firebase was implemented. We used Firebase’s ml kit for text recognition. The ml kit used cloud models for machine learning. The user data is then stored in firebase storage so it can be retrieved the next time the user logs in. We used Firebase because it lets us see the analytics of our application and see where our application had flaws, Which makes our workflow faster especially in a very short amount of time.
Challenges I ran into
One of the challenges we ran into was the use of Google-Vision's text-to-text detection API. When we had first added the dependency the code would crash. With the help of Firebase's Crashalytics, we were able to pinpoint where the error was in the code and exactly which line it was in. Firebase told us what the error was and the Logcat helped us further solve the problem with the error message.
Accomplishments that I'm proud of
I am proud of having a working app that works as intended. I am very happy that the APIs are working and I most happy about the experience that came along with it. We learned many new things such a how to use many technologies with Firebase and how to connect apps.
What I learned
I learned how to use APIs and Firebase. I also learned much more advanced Kotlin and Java.
What's next for LifeLine
We plan to make our machine learning model better by training it with different derivatives and synonyms for the user so the user doesn't have to remember all of the allergies they have.
Our project doesn't fall in a specific category, it has been approved by an organizer that we put it in another category and we have put it under sustainability.