Mason’s Status Report for 10/20
This week, I focused on significant front-end enhancements for the EmotiSense web app. These updates improve user interaction and provide better feedback on emotion recognition results. Specific updates are:
- Added individual views for each of the six emotions (happiness, sadness, surprise, anger, fear, and neutral), allowing users to see a dynamic visual representation for each detected emotion.
- Implemented a display for the confidence score alongside the emotion, which helps users gauge the accuracy of the detection.
- Created logic to track and display the time elapsed from the last emotion transition, offering insight into how quickly emotions change during a session.
Additionally, I spent time researching how to make API calls directly from the Nvidia Jetson Xavier AGX. This research focused on how the Jetson communicates with cloud services and how it handles real-time emotion data processing efficiently. Key learnings included optimizing the use of TCP/IP protocols and managing data transmission with minimal latency.
Is your progress on schedule or behind?
My progress is on schedule. The front-end enhancements have been successfully implemented, and I have made significant progress in understanding how to integrate the Nvidia Jetson for real-time data transmission.
What deliverables do you hope to complete in the next week?
- Finalize API integration design to enable real-time data processing between the Nvidia Jetson Xavier AGX and the cloud-based web app.
- Conduct latency testing to ensure the system can handle real-time emotion data efficiently.
- Further enhance the user interface with responsive design elements and user feedback on system performance.