This week, I worked on finishing up the frontend implementation. On the home page, I interfaced with the backend data, connecting the live wait time and the predicted times for the day based on the ML model. I added the component of having the wait time change color based on the value – if the wait time is <= 10, the wait time will be in green, if it is between 11 and 25, it will appear yellow, and if it is above 25, it will be red. I also added an alert to notify a user that their form input was successfully submitted. This is the updated site when hosted locally, fit for the dimensions of a mobile device. The video was recorded at 12:10 PM on March 25th, which is why the first input is invalid. Notice how the graph shows only values from 12 PM onward. This is an attempt to make the graph as large as possible for the user, as they will not need predicted values for times that have already passed today.
I am on schedule for the week. For next week, I plan on working with Sophie to update the accuracy of our ML model. We also plan to work heavily on the connection of the RPi to our Django server in order to properly receive data from the RFID readers.