Only 25% of Edinburgh Uni students, on average, consume their 5 a day, according to a 2015 survey by the Healthy University
We conducted a survey of 47 undergrads in self-catered accommodations and focus groups of 5 students from 4 different housing units. Almost 75% of students said they cooked for themselves atleast 5 times a week. The general consensus was that students did care about healthy eating but their main limitations were cost, time and energy.
We therefore thought of designing a solution that was healthy, quick and cheap. We believe that the ease of accessibility offered by our product will help students voluntarily make better food choices.
What it does
The android app picks a random recipe for you based on your height, weight, age, gender and activity in a week (in accord with the calorific intake of the meal). The recipe view page has cooking instructions and the ingredients with their quantities. It also has an option to add all the ingredients to a shopping list, from which individual items can be removed by long pressing on them after they have been bought. The recipes were carefully curated taking in consideration the health viability of the ingredients.
The alexa skill will read out the instructions and ingredients from our database to the user. It allows the user to pause and repeat steps as well.
How we built it
We used android studio and the Kotlin programming language to build the mobile app. We scraped and analysed our recipe database using python and a few data visualisation libraries, and built the alexa skill using python and amazon web services.
Challenges we ran into
None of us are seasoned android developers, so we all had a tough time dealing with the finer details of building a good android app. One of our key team members fell sick 2 days before the hackathon and could not make it unfortunately, so we had to distribute the workload of 4 among 3 people. Collecting the data and modifying it to suit our requirements was probably the toughest challenge of them all. Reading the data into our app also took a considerable amount of time as we wanted to find the quickest way.
Accomplishments that we're proud of
We were able to deliver a product that we feel good about. We feel like we made the most of the 24 hours that we had in terms of data collection and analysis and software engineering that we did.
What we learned
Pressure programming and the complexity of android development. We also learnt how to delegate tasks efficiently according to our individual capacities, and learnt about the outliers and problems that come while dealing and analysing large amounts of data.
What's next for GoodEats
We will be expanding our data and recipe preferences to budget, mood, cuisine options and dietary requirements. We feel that having a backend for our app will easily help us process the large amounts of data. We hope to expand the shopping list with the Tesco and Visa APIs to help the users view and order their ingredients through the app. We could also add payments to Alexa.