Our diet as college students look all too familiar - instant noodles, coffee, pints of ice cream, granola bars, and frozen meals. We often settle for the most convenient meal or snack, without thinking about how our emotions can negatively influence our food choices. Rather than getting energized, overly sweet granola bars result in more tiredness and sudden drops of energy levels. Instead of bringing convenience, frozen foods ensue bloating and long-term digestive issues. Our emotions influence what we decide to eat, and this becomes an issue when we don't know what foods can prolong our state of happiness or bring us to a state of relaxation when angry. Why not create an application to solve an issue many of us are facing? And one that makes suggestions that are mentally and physically beneficial for our bodies?
What It Does
Food4Mood is an emotion recognition web app that uses facial expressions. When a user is on the website, he/she is prompted to take and submit a photo for examination. Upon obtaining image data, Food4Mood analyzes what facial expression is most heavily conveyed in the photo and the program recommends various food options to boost the user's mood, whether it be happiness, sadness, anger, surprise, disgust, and even neutral.
How We Built It
Challenges We Ran Into
- Communication between front and backend web development
- Not all members had expertise on the chosen programming language for our project
- Identifying data structures used to store our information
Accomplishments That We're Proud Of
Not having known each other before AthenaHacks, we are pleased with how well we worked together and translating that into a tangible product. All members have never had any hacking experience before, and we are incredibly proud we built an emotion detecting web application using facial expressions in less than a day.
What We Learned
- Working with cloud services, more specifically, Microsoft Azure
- Working with facial recognition
- Creating a web app
- Implementing APIs
- Working with Flask Python
- Application deployment in the cloud
- How to develop and build a product in less than 24 hours
What's Next for Food4Mood
- Taking into consideration age, pregnancies, and dietary restrictions before suggesting foods to consume. While we have kept those with dietary restrictions in mind, we want to explicitly state these in the food recommendations.
- Incorporating age estimations to analyze which foods are best to recommend for which age demographics.
- Further developing our program to add a speech-to-text feature. Instead of requiring the user to take a photo, one can simply verbalize how he/she is feeling to get food recommendations.
- Creating a mobile interface that displays the same application through a chatbot. This would offer a more convenient and quicker experience, rather than having them visit a website.