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https://github.com/faiz-fs/attendance-management-system
An IoT enabled Mobile application to manage attendance based on barcodes for students inside the class and provide live monitoring on a campus can be a useful tool for educators and administrators
https://github.com/faiz-fs/attendance-management-system
dart face-recognition firebase firebase-admin firebase-auth firestore flutter opencv python raspberry-pi-3
Last synced: 9 days ago
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An IoT enabled Mobile application to manage attendance based on barcodes for students inside the class and provide live monitoring on a campus can be a useful tool for educators and administrators
- Host: GitHub
- URL: https://github.com/faiz-fs/attendance-management-system
- Owner: Faiz-fs
- Created: 2023-05-26T04:27:39.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2023-05-26T05:25:42.000Z (over 1 year ago)
- Last Synced: 2024-10-18T04:44:13.453Z (30 days ago)
- Topics: dart, face-recognition, firebase, firebase-admin, firebase-auth, firestore, flutter, opencv, python, raspberry-pi-3
- Language: Dart
- Homepage:
- Size: 1.64 MB
- Stars: 2
- Watchers: 1
- Forks: 1
- Open Issues: 0
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Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Attendance-Management-System
Developing an IoT enabled Mobile application to manage attendance based on barcodes for students inside the class and provide live monitoring on a campus can be a useful tool for educators and administrators. With this application, educators will be able to track attendance in real-time and ensure that all students presence in class. In this application will use barcode scanners are used to detect the presence of students inside the classroom. Students will be issued unique barcodes, which they will scan upon entering the classroom. This information will be sent to a central server and then transmitted to the Android application. Educators will be able to see a list of all students in the class, with their attendance status indicated in real-time and it will provide alerts if a student has been absent for a certain number of classes, allowing them to staying on track.
HARDWARE SPECIFICATION
Microprocessor : Quad-core ARM Cortex-A72 64-bit SoC @ 1.5GHz.
Storage Drive : 32 GB Sandisk SD-Card
Camera module : MIPI CSI Camera
Toolkit : Raspberry Pi 4 Model B, Bar-code Scanner
SOFTWARE SPECIFICATION
Operating System : Kali Linux
Languages used : Flutter, Python
Database : Firebase
Block Diagram of the System
SCREENSHOTS
