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ATTENDANCE USING FACIAL RECOGNITION
Inspiration
We were inspired to create an attendance monitoring system due to extended wait times with biometrics, leading to students skipping the process. My aim is to streamline and improve efficiency in attendance marking.
What it does
My project captures students' faces, marking group attendance efficiently for 3 or 4 individuals. It incorporates fraud detection, identifying and preventing spoofing through photos and videos.
How we built it
Our system, employing the Python face recognition library, captures face encodings for attendance, detecting and preventing fraud attempts like spoofing. Student logs are updated in MySQL, marking presence and time stamping for accurate records.
Challenges we ran into
A challenge we may encounter is inaccurate results in low light conditions. To overcome this, we propose using a small flash during attendance to ensure optimal face detection and enhance accuracy.
Accomplishments that we're proud of
What we learned
We've learned to leverage Python documentation effectively, emphasizing exploration for efficient results before relying on the original source.We've mastered the art of fully utilizing resources and discovered that effective brainstorming can lead to significant achievements in our learning journey.
What's next for ATTENDANCE MONITORING SYSTEM
Our attendance monitoring system can be extended to MNCs and universities, leveraging advanced security cameras for efficient tracking of employees or students in their environments. This allows heads to monitor and access data on individual activities, ensuring a comprehensive and secure approach to attendance management.
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