Eating one more chocolate cup cake a day costs a person 1 hour in a gym. From the perspective of a healthy lifestyle, it is more efficient and important to be able to control food intake in order to live healthily. One of the obstacles is the low awareness of eating habits. People often do not pay attention to the ingredients or find it difficult to track and count calories. Our mobile app solves this problem by firstly providing a quick way to track food intake and the amount of nutrients it contains, and secondly by motivating a person to maintain a healthy lifestyle and achieve new goals.
What it does
The mobile app allows the user to take a photo of the food and, with the help of an external API for food recognition, it provides information about the nutritional value and calories in the food. Through interaction with the user, the app confirms the type of food and clarifies the size of the portion. Afterwards, the record can be saved in the diary, which tracks the user's eating behavior. The app can find out the user's profile by survey questions such as age and lifestyle, but in the future it will also be able to use mobile phone sensors such as the activity level during the day. The health user profile is used to estimate a daily calorie intake and assign a score. The score is translated into game points, motivating the user to maintain healthy behavior by collecting strikes and rewarding consistent and persistent behavior. The app maintains a positive mood using the potatoes theme, as the positive emotions help to overcome temporary hurdles and stay on track. We plan to extend the app in the future to include machine learning about the user personality (stable characteristics such as extraversion or openness) and also more transient states (such as mood swings during the day). The monitoring of the user's state will make it possible to select the most appropriate moments for the implementation of interventions in the form of notifications that provide healthy recommendations to the user (e.g. exercise tips, recipes, nutritional recommendations).
How I built it
We used the framework of React Native and Expo to build a prototype. For the future we plan to extend it to the server backend (e.g. Node JS or Python), which will collect the information and implement machine learning models to evaluate the intervention times and the recommendation system.
Challenges I ran into
In the beginning we investigated the possibility of using Mobile Coach for our purposes, but then we had to change gears and switch to the Expo Framework. It became clear to us that we wanted more flexibility for our purposes and not to stay within the limits of a chat application. The other challenge was to clarify how the external API would work, but in doing so we got the full support of partners from CSS.
Accomplishments that I'm proud of
We are proud of the fact that despite some technical challenges, we persisted and always worked as a team.
What I learned
We learned to work efficiently in a short time, we learned how to work with new APIs and got motivated to learn new things.
What's next for Potato Heroes
We want to integrate the information about physical activity into the feedback the app gives a user. We also want to train and use our own models so that the app can learn more user-specific information. The next sequel to Potato Heroes will make everyone believe that “if you are a couch potato, it's time to rise and be a hero".