The most significant risk is the hand gesture/movement detection system. Since we plan to use our own data set and train our network, it could be more time-consuming than expected. As a contingency plan, we found two pre-trained gesture recognition models online: Real-time-GesRec and hand-gesture-recognition-mediapipe. However, these models do support more gestures, so we will only use a subset that maximizes the detection accuracy.
So far there are no changes made to the existing general design of the system. However, we did introduce a plan B to some of the subparts in the system. For example, we are considering the possibility of using a pre-trained model in case we are not able to collect enough data in a short period of time and train our own. This a necessary precaution to ensure that a problem in one part of the process would not cause the overall hand gesture recognition component of the system to not function properly.
No updates to the current schedule have been created. Currently, we are still in the process of designing our implementation and finalizing design details.
Although we are still in the research and design stage, we did come across a DIY Python synthesizer tutorial that actually mimics the theremin quite well.
Our project includes environmental and economic considerations. We added an autonomous lighting system so that our instrument can function in a very dim environment. We also want our end product to be significantly cheaper than theremin on the market, which limits our budget to be under $400 dollars.