Team Status Report for 2/8/2025
The most significant risks to the success of our project is the performance of the two image classification models and the integration of the hardware components. The accuracy of the image classification models need to be consistently high enough during real world testing in order for the helment to be able to transition between the two image classification and object detection states. The other issue is if the sensors we use will be compatible with our chosen microcontroller, the Jetson Nano. If, for example, the output of the camera is too high resolution and takes up too much memory, then this could be a problem for the limited memory on the microcontroller. These issues are still unclear since the ordered parts have not arrived yet, but the contingency plan is to simply try other parts such as lower resolution cameras that are still clear enough to be used for accurate image classification. No changes have been made to the existing design yet, as we have only just begun the implementation process and no issues have been discovered as of yet.