Food for All

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  The landing page which contains register options for restaurants and shelters.

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  The transaction match page which features the top ranked shelters and their locations relative to the restaurant.

Inspiration

Reducing North American food waste.

What it does

Food for All offers a platform granting the ability for food pantries and restaurants to connect. With a very intuitive interface, pantries and restaurants are able to register their organizations to request or offer food. Restaurants can estimate their leftover food, and instead of it going to waste, they are able to match with food pantries to make sure the food goes to a good cause.

Depending on the quantity of food requested and available to offer as well as location, the restaurants are given a list of the pantries that best match their availability.

How we built it

Food for All is build using a full Node.js Stack. We used Express, BadCube, React, Shard and Axios to make the application possible.

Challenges we ran into

The main challenges of developing Food for All were learning new frameworks and languages. Antonio and Vishnu had very little experience with JavaScript and nonrelational databases, as well as Express.

Accomplishments that we're proud of

We are very proud of the implementation of the Google Maps API on the frontend and our ranking and matching algorithm for top shelters.

What we learned

We learned how to make Rest APIs with Express. We also realized a decent way through our project that our nonrelational local database, Badcube, worked best when the project was beginning, but as the project scaled it has no ability to deal with nuanced objects or complex nested relationships, making it difficult to write and read data from.

What's next for Food for All

In the future, we aim to work out the legal aspects to ensure the food is safely prepared and delivered to reduce the liability of the restaurants and shelters. We would also like to tweak certain aspects of the need determination algorithm used to find shelters that are at greatest need for food. Part of this involves more advanced statistical methods and a gradual transition from algorithmic to machine learning oriented methods.

Built With

• axios
• badcube
• express.js
• javascript
• node.js
• react
• shard