Created in 2019 for the Internet Applications and Web Development course.
For this group project we were to create an application from the ground up for a small business of our choosing. We decided to create a web application where users were able to rent and list parking spots around London, ONT for other people to rent. With a total of six of us working on this project, we named our application Pin Parking, with everyone working frontend, backend and having a hand in the design of the application.
For the backend we used a combination of MongoDB and Laravel where we stored user and listing data. For each listing we pulled out the corresponding data and listed it on the front/landing page where the user can see what the parking spot looks like, where it's located and its renting cost. We kept the design nice, clean and simple while using Bootstrap and implementing a tile system that made information easy to find and legiable. You're also able to sort the listings to better suit your needs.
This is the page if the user were to click on an ad wanting more information about it. There's a large image of the parking spot that's for rent, a small description and a Google Map showing the location of the spot underneath. The user is able to contact the lister via email within the app or by phone. Once the user has made their decision on which parking spot to rent they can book the spot which leads the user through a step by step payment process.
This is where the user is able to view listed spots within a radius of an address. The user puts in a address and selects a radius from the dropdown and the map is then populated with listings with the parameteres given to it. We replaced the default pin with the same pin that we used in our logo to keep consistent with our design. Once the user clicks on a pin the renting price and address is listed with a button that once clicked takes them to the full page listing.
This stats page was something extra that we decided to include in the final. It has two graphs, one showing which users use it most often and another showing which days are users most active on the app.