This week was a productive week for our team. We have continued training our model to improve our accuracy from about 70% to about 80%. We also made good progress in continuing to test and calibrate our ultrasonic sensors and connecting them to RPi. We also have started testing the compatibility of our iOS app with Apple’s accessibility features.
We ran into a risk this week. The Jetson Nano has suddenly started to be stuck on boot up and not proceed to its environment. Since the model has reached the end of life, there is very little help on this issue. We have temporarily switched to the Jetson Tx2 as there is more help for it, but we plan to try again with a different Jetson Nano concurrently. We prefer the Jetson Nano as its size works well for our product.
As a result, we are slightly behind schedule but hope to catch up this coming week. In addition, we haven’t made the decision to switch to the TX2 Jetson permanently, so our design remains the same.
Verifications and Validations
As a team, we hope to complete several validation tests this week. The first test we hope to do is on the latency. This end-to-end latency test will measure the time from when the Ultrasonic Sensor detects and object and when the audio message regarding the object is relayed to the user. We also hope the measure the time from when the camera takes a picture of an object and when the audio message on the object is relayed to the user. We hope to have a latency of 800 ms for both pipelines,
In addition, we hope to do user tests within the next two weeks. We hope to create a mock obstacle course and test the functionality of the product as users complete the obstacle course. We first hope to have the users do this obstacle course with no restrictions but solely for user feedback. With good success of this test, we hope to have users blindfolded and complete the obstacle course entirely relying on the product. The obstacle course will have several objects that we have trained our model for as well as objects that we have not. This will help us test objects that are known and objects that are unknown, but both should be detectable.