Hi, welcome to week 5, where the project faced multiple challenges. This week I started off the weekend with more 3D prints, mainly tweaking measurements in the prints. Below are images of the 3D print series I have compiled, keep in mind that is not all of them! This will be an ongoing theme where I will most likely still be doing tweaks to parts. I do still have to print out a part to finally replace the water bottle as a hopper and support for the entire structure itself. This will be done while I complete other parts of my project, as they will take long hours or even days.
Continuing with 3D printing, I was able to test the two model types more at the beginning of the week. I have established that I will be using the spiral mechanism. The reason behind this is because it jammed the least and when I printed a bigger version. This design was much smoother with testing and is now able to support substances from small grains of sugar to pinto bean size. Below I have included images of the spiral in its case with a rod through it and the view from different perspectives. I will have to reprint the black lid because it is currently on the looser side than I want.
Apart from 3D printing, I started to look into the implementation of the Alexa and Arduino. There were a lot of technical issues beginning with finding MAC addresses for them to register them on the college’s network. From there I was having difficulty trying to think of a way to connect my voice measure skill to the skill that many online sources were indicating that I needed to use in order to connect to the Arduino. At this point, it was later in the week and I know I need to move quickly. We decided that it was best to move on using a Raspberry Pi and the speech recognition Google API that a fellow DTSF peer is already using. This way it would be easier to connect audio and the motor components. I did have slow progress with this because I was also out for a day due to sickness. I also had difficulties with the Raspberry Pi, because although it is not the fastest alone, it did have issues with overheating and freezing the screen altogether. The lesson is to safe progress often. I started with the PyCharm IDE, which was recommended by peers, however, I think the Raspberry Pi was not responding kindly because of it. Therefore, I did have to switch to a different IDE, VSCode. I have used this IDE previously, so it was easier to work with. After many mishaps and technical issues, I finally got the Raspberry Pi to pick up on speech recognition. I will have to develop this code further next week to be able to cut the string that the audio picks up to be able to tell how much the user wants to measure and what they want to measure. I also got all the chords to the stepper motor, Raspberry Pi, and power to be all set. I have now to work on making the stepper motor working, which will be the first thing I do next week. Then the task is to implement these two components together and start calibrating to the different substances. Stay tuned for next week’s progress!