Jam | Devpost

Inspiration

We were inspired by the drastic consequences that Covid-19 has had on local restaurants and the population of low income individuals who have been displaced and have a lack of disposable income. We decided to provide a solution that would utilize the large amounts of food wasted each year by American restaurants to feed those who do not know where their next meal may come from. We wanted to provide a secure and efficient way for those with low income to find and access food nearby.

What it does

Jam is a website where restaurants and companies volunteer to donate food and supplies to impoverished people. Afterwards, a corresponding app can be used by the aforementioned impoverished people to find locations to pick up supplies and resources. Jam will assist low income families and provide information for restaurants about potential food waste.

How I built it

We built the website using HTML/CSS and JavaScript to create a login page as well as a modern dashboard to view current sales and information. Using Jupyter Notebook we were able to build a machine learning algorithm to maximize the products a restaurant is selling to reduce potential waste as well as provide a source to locate resources nearby to donate these items. We connected these pieces together to build out the final website and plan to implement the features of the user app to receive food from these various restaurants and volunteer shelters.

Challenges I ran into

One major challenge we ran into was creating the machine learning algorithm based on the data created from several resources and research that we had compiled based on real restaurant sales. It was difficult to create an accurate prediction but found an eventual solution through using a linear regression model.

Accomplishments that I'm proud of

We are proud that we were able to create an idea that is able to cover several topics of concern in the world right now such as local restaurants, homeless or recently displaced individuals from the effects of Covid on employees, and environmental concerns involving the mass amounts of food that is wasted. This product helps solve several problems and we were proud we were able to create this idea and provide an efficient solution.

What I learned

We learned how to implement a machine learning algorithm using the data we had created and use a linear regression model to find the optimal solution for restaurants to maximize their product amounts to avoid waste as well. We also learned more about how to implement graphs in JavaScript to create a dynamic website.

What's next for Jam

The next steps are to build out the Recipient App that allows users who need access to food and other types of resources to find them based on their current location. This would connect with the website and create a seamless transition between availability of food and potential food waste and those who are in need of these items. We plan to build this out using React Native and create a desktop app as well.