James G

This learning module, James used a Raspberry Pi, Node.js, Electron, and Android Studio to create a clone of Alexa. With it you could ask questions, ask it to send emails, ask it to play a song or a video, and more. With  it James also created an app that allowed you to connect to it using Bluetooth.

Final Write-Up

In this learning module, James and Wesley attempted to get an Amazon Alexa to communicate with an Arduino. The Arduino they had did not have wi-fi capabilities. So instead they used a Node MCU. However, this was a 5-day learning module and James missed a day. They had everything with the Alexa working and all the code finished for the Node MCU but were never able to compile before the last day of the learning module.

Final Write-Up

This learning module, James and Aidan created a Raspberry Pi ID scanner that would keep track of those who scanned there id and everyone would have their own page on a website where you can see data for when they came in and left the room. This ended up being successful and they were able to use a Rapberry Pi Zero W to communicate with a server that had a website hosted on it that would have the data for those who scanned their ID's.

Final Write-Up

This learning module, James and Walter would learn how to use the Xbox Kinect and would create a game with it. They in the end created a version of Pong where the user would control a paddle using their arm. The game was for two players, the player on the left used their right arm and the player on the right used their left arm. This was created using Unity.

Final Write-Up

This learning module James and Yuliana combined a lot of different things to make ASLgo. They used their knowledge of web development and new knowledge of AI (Tensorflow). On top of that, it was made into a website, aslgo.jamesgoo.de, that can be reached by anyone wanting to try it.  It works as a way to teach people American Sign Language and provide resources for it, which we found hard to find online.  We used TensorFlow and joint calculation to work out what sign hands in front of a laptop's camera. (CAMERA DOES NOT WORK ON THE LEFT AND MUST OPEN IN NEW TAB AT aslgo.jamesgoo.de)

Final Write-Up

This learning module James and Ryan attempted to create a VR Game in unity. Due to the pair being absent from school most of the time they did end up splitting up in the end. James ended up with a prototype for a VR programming game in which two players attempt to solve programming puzzles in javascript. One player is in VR and the other is on a computer. The VR headset used is an Oculus Quest 2.

Final Write-Up

This learning module James and Yuliana attempted to make an old Pharmaceutical Arm that originally came with nothing but the machinery, do things. They originally wanted to make it play chess, but in the end decided to switch to Tic Tac Toe as it was simple, faster, and better for the range of motion for the arm. On the left is a video of our school's principal playing against the arm. An Ai is deciding the moves for the other player. 

Final Write-Up

This learning module James and Yuliana would attempt to create a bunch of little websites. Each of these websites would be unique in what they could do and would have there own purposes. During the course of this learning module the main struggle would be with coming up with ideas for these websites. Everything either felt too simple or too much for a website marathon were we were going to make a bunch of websites. On the left here are two websites, one that does calculus approximations, such as limits, derivatives, calculus, and arc length, and another website that is a call website where people's faces are on cubes when they join the call (CAMERA DOES NOT WORK ON THE LEFT AND MUST OPEN IN NEW TAB AT cube.jamesgoo.de). 

Final Write-Up

This learning module James and Yuliana would attempt to make an app that converts notes from a photo to text and then would store this text in data. After you could then turn these notes into various study materials such as flashcards, mini-quizzes, and a slide presentation. The app was very successful and yielded mostly consistent and helpful results. On the left is our presentation, on one of the slides near the end there are 4 videos of it working as intended with very promising results.

Final Write-Up