Good Food

The Good Food app helps to facilitate a sense of sustainability coupled with striving towards living a healthy lifestyle.

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Inspiration

Every person is different, and each one has different wishes, preferences and desires.

Research from Food Watch highlights that consumers are looking for different aspects of Honest Products, such as Nutritional Quality, Carbon Footprint, Organic, Vegan.

Manufacturers can't possibly print everything on the pack and some marketing claims may be misleading. Brand owners and retailers are not able to provide each consumer with relevant insights in an individual level, at the moment they are buying their groceries.

Producers and retailers need more insights about the consumer's decision making process and their preferences + Consumers need information at the right time to help them make a sustainable choice, given their food restrictions and health concerns

Sustainable Development Goal (SDG) #2, defined by the UN, is focused on ‘Zero hunger’ and includes ‘End hunger, achieve food security and improved nutrition and promote sustainable agriculture’.

What it does

We have introduced a platform wherein each user can choose their own products which are align with their values and goals in life.

The points that they achieve in this process and sharing with friends will in turn motivate them to follow their daily routine.

It allows users to select aspects of products which are important to them, such as:

  • Nutriscore
  • Organic
  • CO2 footprint
  • Plastic-Free
  • Vegan
  • Gluten Free
  • etc

Then user can clearly see how the products they want to purchase compare across those attributes.

They are also able to see how they are doing against their chosen goals and share success with friends.

How we built it

JavaScript, React, Python, Atrify API, Google Cloud, Flask

Challenges we ran into

Tricky to get product-level CO2 footprint. Nutriscore information is not always perfect. Defining fresh products is only possible with access to "use by" dates.

Accomplishments that we're proud of

In just a few hours we've extracted relevant data from a new data source (Atrify) and built an clear and intuitive tool.

What we learned

What's next for GoodFood

  • Include a location-wise grouping of retailers who sell sustainable products
  • Include more dimensions for customers to select
  • Improve CO2 calculations
  • Explore Epo s ystem integration

Slides: https://speakerdeck.com/meiradania/good-food-presentation-gs1-hackathon-2020-09-19-b9808cb9-ab13-4925-bebe-ff545e5220e3

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