Team’s Status Report 11/9
1. What are the most significant risks that could jeopardize the success of the project?
- Model Accuracy: While the model achieved 70% accuracy, meeting our threshold, real-time performance with facial recognition is inconsistent. It may require additional training data to improve reliability with variable lighting conditions.
- Campus network connectivity: We identified that the Adafruit Feather connects reliably on most WiFi networks but encounters issues on CMU’s network due to its security. We will need to tackle this in order to get the Jetson and Adafruit communication working.
2. Were any changes made to the existing design of the system?
- AJAX Polling and API inclusion for Real-time Updates: We implemented AJAX polling on the website, allowing for continuous updates from the Jetson API. This feature significantly enhances user experience by dynamically displaying real-time data on the website interface.
- Jetson Ethernet: We have decided to use ethernet for the jetson to connect it to the cmu network.
3. Provide an updated schedule if changes have occurred:
The team is close to being on schedule, though some areas require focused attention this week to stay on track for the upcoming demo. We need to get everything up and running in order to transition fully to testing and enhancement following the demo.
Photos and Documentation:
- Jetson-to-website integration showcasing successful data transmission and dynamic updates. emotisense@ubuntu is the ssh into the Jetson. The top right terminal is the jetson, the left and bottom right are the website UI and request history respectively. I also have a video of running a test file on the jetson but video embedded doesn’t work for this post.
