Introducing

Vendi

a vending machine locator app

What is it?

CS 426 Senior Project in Computer Science, Spring 2023, at UNR, CSE Department

Simply put, our app is used to find vending machines within a short location of the user. Using google maps, a sleek AI, and a growing database, users will be able to locate vending machines anywhere within a specified radius around them. We also allow users to filter machines based on their needs. Whether you're looking for drink machines, snack machines, or even school supply machines. If there is one around you, you'll know it with Vendi. On top of this, users will be able to contribute Vending Machines that aren't already added to the database. This will allow them to accrue points that can be redeemed for real money and allow us to keep our database as up-to-date as possible.

What technologies did we use?

Vendi is a mobile, cross-platform, app developed using the Flutter framework developed by Google and written in their programming language, Dart. We've used a handful of Flutter plugins to develop our front-end, and develop our backend connection. The most important of these plugins has allowed us to implement Google Maps into our app! Our backend uses two primary technologies, Firebase and Flask (in combination with Tensorflow). Firebase is used throughout the majority of our app. It allows people to create secure accounts and it stores all of our data, from user data, user favorites, and our database of machines. Flask and Tensorflow are used in conjunction with our crowdsourcing feature to help make sure actual machines are being uploaded to our database. Flask is used to help Tensorflow function as an interpreter for the model that was also built using Tensorflow.