We wanted to put together something that could help others prevent diabetes and something that could help those affected get the help they need. We have a friend who is diabetic, and we understand the difficulty of living with this condition.
What it does
Our web application helps users track their diet. Users are prompted to input some information about themselves. Using that information with a dataset of diabetic patients, we generated a graph showcasing the relation between age, blood sugar, and diabetes. We also, provide the functionality to let the user input in their daily meals. Then, our application processes that, and gets data on the carbohydrates and calories in that meal. We aggregate that data into graphs, which will hopefully give the user a big picture of their dietary habits. Finally, our application connects users with nearby health centers if they are in need of professional attention.
How we built it
We first retrieved data on over 100,000 diabetic patients, who were affected with diabetes in the past 10 year. Using this data, we processed that data to find the relationship between age, sex, race, and the chance of getting diabetes. Then, we used the FatSecret API to retrieve data on food the users would input into our application. This API provided us with a huge source of information about all sorts of food and their nutritional information. Our application processed that data appropriately, giving the user an accurate representation of their daily consumption. Finally, we aggregated data on health centers to give the user information on nearby health centers based on their location. We dealt with big data. In the back end, we stored this data on a MongoDB service running on a Ubuntu AWS machine. Our web application, written in Python with Flask, accessed that data for our users. More importantly, we visualized data using Chart.JS to give users a friendly experience.
Challenges we ran into
Some challenges we faced were implementing everything together: -Connecting to a MongoDB -Using Google Map's API to display a map
Accomplishments that we're proud of
The beautiful user interface that makes this application very usable and friendly. Using MongoDB and processing a huge amount of data in a short amount of time.
What we learned
We learned a lot of diabetes and the affect of food intake on it. Specifically, we learned about the glycemic index, and how different foods have different affect on blood glucose throughout the course of the day. In terms of computer software, we learned a lot about accessing APIs, using different types of them (XML, JSON). We also learned a lot about data visualization and how to present a lot of data to users.
What's next for Dietbetes
Our next steps include the following: -Continuing to work on providing ways to help the user with their health needs -Providing more meaningful data for the user