This week we succesfully managed to deploy the web app to AWS as well as test that our app works on an Android phone. Getting the app to work on a smartphone versus a computer was one of the risks we had, so this risk has been eliminated now that we know the app works on a smartphone.
The most significant risk we still face is getting persistent Bluetooth to work, as this would reduce the time the user spends needing to connect to the Raspberry Pi every time they open the app. Currently, we are working on creating an Android applet, which will maintain the Bluetooth connection while the web app is closed. In addition to this risk, our other risks include integrating the item recognition into our app, as currently we are running the web app and the ML item recognition on two different servers, and getting the servers to communicate may be difficult.
As for design changes, we have decided not to implement the sleeping protocol for the Raspberry Pi, as we have determined that even under the most demanding conditions the battery life is sufficient to run the system for at least two 8-hour work days, or one 18-hour day. Additionally, even if there are no events scheduled, the user may want to check their items arbitrarily, and they would not be able to do so quickly if the system is asleep given the long bootup time of the Raspberry Pi.
The only major change to our schedule is that we are increasing the time for the persistent Bluetooth problem. As always, our schedule can be viewed here.