ELA Component

August 17 - August 31:

• Began researching different libraries and frameworks for building our facial recognition attendance system

• Decided to use dlib, face_recognition, and pyQt for the user interface.

• Set up virtual environment

• Set up our development environment and installed pyQt, CMake, dlib, and face_recognition

• Began working on the user interface using pyQt

• Continued working on the user interface and started integrating the facial recognition functionality using dlib and face_recognition

• Successfully implemented basic facial recognition functionality, including the ability to detect and recognize faces in real-time video feed

• Began working on attendance tracking functionality, including the ability to mark students as present or absent based on their facial recognition

September 1 - September 14:

• Continued working on the attendance tracking functionality and added the ability to save attendance records.

• Began testing the facial recognition system with a small group of students to ensure it was accurately detecting and recognizing faces.

• Adjusted tolerance of the facial recognition system to be more strict

• Made some improvements to the user interface based on feedback from our testing group.

• Continued testing and refining the system.

• Completed the attendance tracking functionality and began working on the reporting and analysis features.

September 14 - September 28:

• Completed the reporting and analysis features, including the ability to generate reports on attendance trends and patterns.

• Conducted final testing with a larger group of students to ensure the system was working reliably.

• Completed all necessary documentation and prepared the system for deployment.

• Added the ability to send an Excel spreadsheet of the attendance report upon request.

• Deployed the facial recognition attendance system to a classroom and conducted a trial run with a full class of students.

October 1 - October 14:

• Reviewed the results of the trial run and made some final tweaks to the system based on feedback from the teachers and students.

• Conducted additional testing to ensure the Excel report feature was working correctly.

• Completed all final testing and debugging.

• Submitted the completed facial recognition attendance system for review and approval.