The Q'd Login/Registration Screen
The Q'd User Profile
The Q'd Venue Creation Form
Queue data analytics in the host's dashboard
Penny's profile in the host queue analytics dashboard
Our Hesura database and server
On our way to PennApps, our team was hungrily waiting in line at Shake Shack while trying to think of the best hack idea to bring. Unfortunately, rather than being able to sit comfortably and pull out our laptops to research, we were forced to stand in a long line to reach the cashier, only to be handed a clunky buzzer that countless other greasy fingered customer had laid their hands on. We decided that there has to be a better way; a way to simply walk into a restaurant, be able to spend more time with friends, and to stand in line as little as possible. So we made it.
What it does
Q'd (pronounced queued) digitizes the process of waiting in line by allowing restaurants and events to host a line through the mobile app and for users to line up digitally through their phones as well. Also, it functions to give users a sense of the different opportunities around them by searching for nearby queues. Once in a queue, the user "takes a ticket" which decrements until they are the first person in line. In the meantime, they are free to do whatever they want and not be limited to the 2-D pathway of a line for the next minutes (or even hours).
When the user is soon to be the first in line, they are sent a push notification and requested to appear at the entrance where the host of the queue can check them off, let them in, and remove them from the queue. In addition to removing the hassle of line waiting, hosts of queues can access their Q'd Analytics to learn how many people were in their queues at what times and learn key metrics about the visitors to their queues.
How we built it
Q'd comes in three parts; the native mobile app, the web app client, and the Hasura server.
Our beast of a server was constructed with the Hasura application which allowed us to build our own data structure as well as to use the API calls for the data across all of our platforms. Therefore, every method dealing with queues or queue analytics deals with our Hasura server through API calls and database use.
Challenges we ran into
A key challenge we discovered was the implementation of Cordova and its associated plugins. Having been primarily Android developers, the native environment of the iOS application challenged our skills and provided us a lot of learn before we were ready to properly implement it.
Next, although a less challenge, the Hasura application had a learning curve before we were able to really us it successfully. Particularly, we had issues with relationships between different objects within the database. Nevertheless, we persevered and were able to get it working really well which allowed for an easier time building the front end.
Accomplishments that we're proud of
Overall, we're extremely proud of coming in with little knowledge about Cordova, iOS development, and only learning about Hasura at the hackathon, then being able to develop a fully responsive app using all of these technologies relatively well. While we considered making what we are comfortable with (particularly web apps), we wanted to push our limits to take the challenge to learn about mobile development and cloud databases.
Another accomplishment we're proud of is making it through our first hackathon longer than 24 hours :)
What we learned
During our time developing Q'd, we were exposed to and became proficient in various technologies ranging from Cordova to Hasura. However, besides technology, we learned important lessons about taking the time to properly flesh out our ideas before jumping in headfirst. We devoted the first two hours of the hackathon to really understand what we wanted to accomplish with Q'd, so in the end, we can be truly satisfied with what we have been able to create.
What's next for Q'd
In the future, we're looking towards enabling hosts of queues to include premium options for users to take advantage to skip lines of be part of more exclusive lines. Furthermore, we want to expand the data analytics that the hosts can take advantage of in order to improve their own revenue and to make a better experience for their visitors and customers.