GrabNOut

Interface of the path for a customers grocery list using Iterative deepening A* Algorithm
Interface of the path for a customers grocery list using Best First Search Algorithm
Customer Shopping List

Inspiration

We were inspired to do this because as consumers we understand how frustrating it can be to find specific items in stores. We wanted to target our product to busy mothers who need to get in and out of grocery stores.

What it does

Our project is a shopping application that helps busy consumers shop more efficiently. The application allows the user to create a shopping list of goods. After the user selects the goods, the UI will help the customer navigate through the store to the grocery items on the list. The project used a shopping list that implemented CRUD functions. The list then connects with the stores to locate where each of those items is in the store.

How we built it

The project was built entirely in React.js using javascript and css.

Challenges we ran into

Our biggest challenge was working with JavaScript, and React. We came into this project with zero web development experience. We had to spend countless hours not only familiarizing ourselves with a new language, JS, but also the React library, which was by far the toughest challenge. Additionally, we had to learn and develop the algorithms used by our project to find the solution to our problem.

Accomplishments that we're proud of

We are proud of designing a working algorithm that satisfies all of the conditions we needed. As well as, learning and completing a daunting project in the React environment.

What we learned

As a team we have all learned an innumerable amount of web development experience, especially in React. We also learned teamwork, designing phases, and the whole SDLC.

What's next for GrabNOut

In the future, we would like to implement a tool that would compare the total cost of the shopping list with multiple stores close by. Then have a google maps API integrated into our app that would find the quickest route to hit all of the stores. We would also like to use data analytics to help store owners learn more about their customers’ shopping habits.