One issue that we have not really spent too much thought on is whether or not the machine learning models will fit on the microcontroller. The microcontroller itself already has a decent amount of memory, but it is possible that we can add external storage as well. The models themselves, from initial research, should definitely fit. Quantizing the models will make them smaller and possibly improve inference speed, but this can sacrifice performance and might not be necessary from a model size standpoint. No changes have been made to the design recently, and next week we should begin to explore how we can upload the models to the microcontroller and being developing the main program that is going to run the models and manage the control flow.
With regards to hardware, testing for integrating the peripherals is still ongoing. We forecast that it will be complete by the end of next week. One piece of good news is that we have confirmed that the USB C PD to DC cable can successfully power the Jetson Orin Nano, which will allow us to make it portable. For some reason, our existing power bank (which was not purchased but had on hand) cannot supply the correct wattage, which is probably due to it being old. We will now need to find a suitable power bank to buy. Initial designs have also started for mounting the Jetson Orin Nano. Based on our last meeting, we have decided to create both a helmet mount and a chest mount. Once complete, we can test and compare both designs for user comfort and camera shake. The testing will determine which mounting system is used in the final design.
With regards to the object detection models, we continue to have trouble with fine-tuning out of the box models. To give a greater range of models to evaluate, we have decided to pause the fine-tuning implementation, and work on evaluating different YOLO models available, such as YOLOv12. No changes otherwise have been made to the software implementation