Solution
Embedded Files
Our team addressed this problem by creating Smarter Bites, a mobile app that helps college students make healthier eating decisions in the moment. Instead of requiring users to plan every meal ahead of time or log everything they eat, Smarter Bites focuses on quick support that fits into the unpredictable structure of student life. Our user interviews showed that students often react to their day rather than plan it. They decide what to eat based on how much time, money, and energy they have in the moment.
The core concept of Smarter Bites is a context based system. When users create their profiles, they can describe their needs as a student in an open-ended way. For example, they can enter their food goals, budget, available cooking time, access to kitchen equipment, preferred ingredients, dietary restrictions, or how easy they want the recipe to be. There are no restrictions. Based on that context, the app uses AI to recommend or generate meals that fit the student’s actual situation. This removes the need for students to spend extra time researching recipes, comparing nutrition information, or figuring out whether a meal works for their budget and schedule.
Smarter Bites also gives students flexible ways to track what they eat without making the process feel overwhelming. Users can track nutrients and meal stats directly from a generated recipe, they can use the camera feature to scan a meal and receive a quick nutrition estimate, or they can directly enter the nutrition information themselves. This design choice came directly from our interviews, where we learned that students prefer a fast and easy estimate over a detailed process that takes more time and effort. The goal is not perfect tracking. To encourage consistency, Smarter Bites also includes a short daily check-in system. Users can build streaks and view simple progress stats, such as meals tracked. This gamification gives students a sense of progress and motivation without making the app feel strict or judgmental. Overall, Smarter Bites is designed to bridge the gap between intention and action by giving students practical, personalized, and low-effort support.
User flow diagram
The user flow diagram above shows how a user might typically use our app from start to finish. The overall interaction would look something like this. The user logs in and completes the check-in to keep track of their progress and usage, then the user updates their profile with their preferences. After that, they can generate recipes and find one that they like. From there, the user can make that recipe and track it using the nutrients listed in the recipe itself. If the user wants to track food not from a recipe, they can decide to take a photo and get an estimate of their meal as well.
Key Features
Dashboard:
The dashboard contains a summary of the user's nutrition information. From this, they can make decisions on what type of foods that they want to eat. The user can also customize what nutrition information shows up on the dashboard screen.
From the dashboard, the user can also access any of the other pages as well. It acts as a hub for navigation to make the experience overall easier. We want our app to be as easy to use as possible to keep users consistent.
Check-in:
This is the check-in screen that users would see, that help to incentivize them to keep consistent and use the app. This is something small that we added to address the consistency problem.
The daily check-in and progress features encourage consistency without making the app feel strict or judgmental.
Profile:
The profile page is where the user enters all the context that they want our app to use when generating recipes. For ease of use, we allow users to talk to type, so that they do not have to manually enter everything themselves. Users can update this page whenever they feel like it to match what they want in the moment.
This allows users to automatically get recipes that tailor to them and their situation. Because there is no limit to what you can put into your preferences and situation, users have the freedom to let the app get to know them as much as they would want. Our app will consider everything that the users input when making recommendations. This is what differentiates us from all other apps.
Recipes:
This is the page where users can see all the recipes that we have. From here, they can either search for recipes themselves, view the ones that we recommended based on their preferences, or check out their saved recipes list.
If the user is searching for a recipe and finds a recipe that they are interested in, they can click into it for more information. Once they click into a recipe, they can see the recipe's information like ingredients, time to make, nutrients, etc. If they like the recipe, they can save it and add it to their saved list.
With this, instead of searching through recipes that may be too expensive or time consuming, students can receive options that already match their needs through our recommendations based on the information that they shared.
Tracking:
This is the page where users can track their meals, see their nutrients, and see the meals that they have already tracked. They can track directly from recipes, manually add in information themselves, or use the camera AI feature to estimate their meal directly from a photo, either uploaded or taken in the app.
The goal was to give users the freedom to choose their level of effort or accuracy when it comes to tracking the food that they eat. This addresses how many students may not want to put much effort in when it comes to tracking food.
With tracking food, the user can see if they're missing any nutrients and what they might want to add more of into their diet.
Rationale
Our team chose to design Smarter Bites as a mobile AI food companion because our research showed that students need support in the moment. While many existing nutrition apps focus on detailed logging, calorie counting, and long-term tracking, our interviews suggested that this does not fit well with student life. Students often make food decisions based on their current budget, schedule, energy level, and available food options. Because of this, we designed Smarter Bites around quick recommendations, flexible tracking, and personalized context.
Research strongly influenced our design decisions. In our interviews, both participants identified time and money as major barriers to eating well, and one participant said, “If it’s tedious, I won’t use it.” This insight directly shaped our decision to make the app low effort. Instead of requiring users to manually search for recipes or log every ingredient, Smarter Bites allows users to enter their preferences once, then receive AI-generated meal ideas that match their situation. The camera scan feature was also designed around this need for convenience, since it gives users a quick nutrition estimate for meals that were not created through the app.
We chose this solution over other ideas because it better addresses the actual behavior patterns of students. A basic meal planner would still require students to think ahead and follow a schedule, which may not work for users with unpredictable days. A traditional food tracker would provide information, but would not help students decide what to eat when they are tired, busy, or limited by money.
We also considered several trade-offs. One trade-off was accuracy versus ease of use. A detailed manual food log could provide more precise nutrition data, but it would also take more time and effort, making students less likely to use it consistently. We chose quick estimates because our research showed that students value convenience and are more likely to engage with a tool that feels simple.
Overall, Smarter Bites is not designed to make students follow a perfect diet. It is designed to help them make better choices within the real constraints of college life. By focusing on context, simplicity, and flexibility, our solution directly responds to the problems identified in our research.
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