Most of our team is indecisive when it comes to picking something to eat, so we wanted something that could help recommend us food to eat. However, most food recommending websites or apps don't take into account your nutrient intake and what you have eaten previously before they recommend you food to eat. Especially as college students, sometimes our diets can become skewed to heavily include certain nutrients over others.

What it does

Nutrient Watchers is meant to help you decide on a meal based on a history of the foods you've eaten in the past few days so that it can recommend foods that are rich in nutrients that you may have missed in the past few days without even realizing it. All you need to do is record what you ate after you eat them, ask Nutrient Watchers for a recommendation when you're not sure what to eat, and then enjoy a balanced meal! You don't even need to know the nutrition facts of what you ate, Nutrient Watchers will use information from the USDA Nutrition Database to find the closest item and add that to your list.

How we built it

The back end was written in Java and Jersey while the front end was written in html and Javascript. We used the USDA's Nutrition Database to retrieve all of the nutrition facts for each food that is requested. Our database is managed by mySQL.

Challenges we ran into

Figuring out how to integrate front and back end together. Creating a user authentication system since none of us had any experience with that.

Accomplishments that we're proud of

Now we can pick something to eat knowing that it will help us keep a balanced diet.

What we learned

Sleep is good. And that there are many different ways to do a user authentication system

What's next for Nutrient Watchers

Beyond expanding the number of nutrients that we keep track of, we wanted to implement an option that you can also look for restaurants that serve the specific meals that we recommend so that you don't even have to cook! In addition, we wanted to use previous user meal history to filter out what foods they would be most likely to want to eat to recommend to them.

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