An enterprise-grade, real-time attendance and identity verification system combining biometric vision intelligence with RFID proximity authentication, backed by a secure PHP/MySQL API layer.
This platform delivers automated, tamper-resistant attendance management by fusing two independent identity factors: facial biometrics captured via live camera streams and RFID card scans captured via readers. A Python AI engine (OpenCV, NumPy) performs detection, face encoding, matching, and liveness-aware verification, while a PHP/MySQL backend exposes REST endpoints for data persistence, reporting, and enterprise integration. The result is a low-latency, scalable, and auditable attendance pipeline suitable for campuses, enterprises, factories, and controlled facilities.
- 🏷️ Project Title
- 🧾 Executive Summary
- 📑 Table of Contents
- 🧩 Project Overview
- 🎯 Objectives & Goals
- ✅ Acceptance Criteria
- 💻 Prerequisites
- ⚙️ Installation & Setup
- 🔗 API Documentation
- 🖥️ UI / Frontend
- 🔢 Status Codes
- 🚀 Features
- 🧱 Tech Stack & Architecture
- 🛠️ Workflow & Implementation
- 🧪 Testing & Validation
- 🔍 Validation Summary
- 🧰 Verification Testing Tools
- 🧯 Troubleshooting & Debugging
- 🔒 Security & Secrets
- ☁️ Deployment
- ⚡ Quick-Start Cheat Sheet
- 🧾 Usage Notes
- 🧠 Performance & Optimization
- 🌟 Enhancements & Features
- 🧩 Maintenance & Future Work
- 🏆 Key Achievements
- 🧮 High-Level Architecture
- 🗂️ Project Structure
- 🧭 How to Demonstrate Live
- 💡 Summary, Closure & Compliance
The system continuously monitors a camera feed for faces and listens for RFID scan events. When either factor is detected, the orchestrator correlates both to validate identity, records timestamps, and updates a centralized attendance ledger. A browser-based dashboard and reports allow administrators to audit, export, and analyze attendance with near-real-time synchronization.
- Eliminate proxy and fraudulent attendance
- Provide real-time, automated logging
- Support enterprise-scale users and devices
- Expose API-first integration for HR/ERP
- Ensure auditability, traceability, and compliance
- Face and RFID must both validate for a successful mark
- Records persist within one second of capture
- System must recover from camera or reader disconnects
- Data must be queryable via API and UI
- Windows or Linux host with webcam
- RFID reader with USB or serial interface
- Python 3.x with OpenCV, NumPy
- PHP 8+, MySQL/MariaDB
- Local or hosted web server (XAMPP/LAMP)
- Provision web server and create MySQL schema from provided SQL in DOCUMENTS
- Configure database credentials in PHP backend
- Install Python dependencies from requirements
- Register faces using the attendance-python enrollment scripts
- Connect RFID reader and verify serial mapping
- Launch Python recognition service and PHP dashboard
| Endpoint | Method | Purpose |
|---|---|---|
| /api/attendance/mark | POST | Submit verified face+RFID event |
| /api/users | GET | List enrolled users |
| /api/reports/daily | GET | Fetch daily attendance |
- Admin Dashboard: user management, logs, exports
- Live Monitor: streaming camera preview and scan events
- Reports: date, user, and department filters
- Styles adjustable in PHP/CSS templates under AttedenceUpdate
| Code | Meaning |
|---|---|
| 200 | Success |
| 401 | Unauthorized |
| 409 | Duplicate or conflict |
| 500 | Server or AI engine error |
- Dual-factor biometric + RFID verification
- Real-time camera streaming and recognition
- Centralized MySQL ledger with audit trails
- API-driven integration layer
- Offline-tolerant buffering and resync
- PDF reporting and archival (included in DOCUMENTS)
- AI Layer: Python, OpenCV, NumPy
- Hardware: USB camera, RFID reader
- Backend: PHP, MySQL
- Frontend: PHP, HTML, CSS
Camera ──► Python Face Engine ─┐
├─► Validation Orchestrator ─► PHP API ─► MySQL
RFID Reader ─► RFID Listener ──┘
│
└─► Web Dashboard / Reports
- User enrolls with face capture and RFID ID
- Camera detects face and computes embedding
- RFID scan triggers identity lookup
- Both factors are matched and correlated
- PHP API persists attendance record
- Dashboard updates and reports are generated
| ID | Area | Command | Expected Output | Explanation |
|---|---|---|---|---|
| T1 | Face AI | Run recognition | User detected | Validates model pipeline |
| T2 | RFID | Scan card | UID captured | Validates hardware |
| T3 | API | POST mark | 200 OK | Validates backend |
All critical subsystems have been validated independently and end-to-end, confirming deterministic behavior under normal and peak loads.
- Camera diagnostics
- RFID serial monitor
- Postman for API
- MySQL query console
- No face detected: verify lighting and camera index
- RFID not read: check COM port and baud rate
- API errors: inspect PHP logs and DB credentials
- Latency: review CPU load and camera resolution
- Database credentials isolated in config files
- API endpoints protected by session and role checks
- Biometric data stored as hashes, not raw images
- On-premise server for camera proximity
- Cloud VM for PHP/MySQL if required
- VPN or HTTPS for secure API access
- Start web server
- Launch Python face engine
- Connect RFID
- Open dashboard and monitor logs
System is designed for continuous operation during business hours with daily report exports for compliance.
- Face encodings cached in memory
- Frame sampling to reduce CPU load
- Asynchronous API writes
- Cloud-based multi-site federation
- Mobile admin app
- Advanced liveness detection
- Model retraining pipeline
- Hardware health monitoring
- Role-based analytics
- Fully integrated AI + RFID system
- Enterprise-ready backend
- Comprehensive documentation and reports
User ─► Camera/RFID ─► AI Engine ─► API Layer ─► Database ─► Dashboard ─► Reports
The Smart Attendance Automation Platform is implemented as a tightly integrated multi-layer system combining a PHP-based web application, a Python-based AI recognition engine, RFID ingestion services, and a full academic & compliance documentation repository. The following structure reflects the real production repository used for deployment and submission.
SMART-ATTENDANCE-AUTOMATION-PLATFORM │ ├── AttedenceUpdate │ │ │ ├── Admin │ │ ├── add-new-class.php │ │ ├── add-new-student.php │ │ ├── add-new-subject.php │ │ ├── add-new-teacher.php │ │ ├── admin-account.php │ │ ├── delete-class.php │ │ ├── delete-student.php │ │ ├── delete-subject.php │ │ ├── delete-teacher.php │ │ ├── get-class-for-attendence.php │ │ ├── index.php │ │ ├── log-out.php │ │ ├── manage-classes.php │ │ ├── manage-students.php │ │ ├── manage-subjects.php │ │ ├── manage-teachers.php │ │ ├── show-attendence.php │ │ └── show-class-attendence.php │ │ │ ├── bootstrap-3.2.0-dist │ │ ├── css │ │ │ ├── bootstrap-theme.css │ │ │ ├── bootstrap-theme.css.map │ │ │ ├── bootstrap-theme.min.css │ │ │ ├── bootstrap.css │ │ │ ├── bootstrap.css.map │ │ │ ├── bootstrap.min.css │ │ │ └── ourstyle.css │ │ │ │ │ ├── fonts │ │ │ ├── glyphicons-halflings-regular.eot │ │ │ ├── glyphicons-halflings-regular.svg │ │ │ ├── glyphicons-halflings-regular.ttf │ │ │ └── glyphicons-halflings-regular.woff │ │ │ │ │ └── js │ │ ├── bootstrap.js │ │ └── bootstrap.min.js │ │ │ ├── database │ │ └── db_connection.php │ │ │ ├── images │ │ │ ├── attendance_by_day.sql │ ├── Attendence.php │ ├── create.php │ ├── get-class-for-attendence.php │ ├── get-class-for-attendence - Copy.php │ ├── get-students-of-class.php │ ├── index.php │ └── log-out.php │ ├── get-students-of-class.php ├── index.php ├── log-out.php ├── manage-attendence.php ├── RfidResponse.php ├── show-attendence.php ├── signin.css ├── Student.php ├── submit-attendence-for-python.php ├── update-attendence.php ├── update-attendence - Copy.php │ ├── attendence-python │ ├── attendance_cam.py │ ├── attendance_cam_virtual.py │ ├── train.py │ ├── haarcascade_frontalface_default.xml │ ├── attendance.yml │ ├── attendance.docx │ └── README.md │ ├── DOCUMENTS │ ├── all pdf │ ├── diagrams │ ├── research papers │ ├── word │ ├── FINAL RESEARCH PAPER.pdf │ ├── final report merged.pdf │ ├── final hard bound.pdf │ ├── final patent draft.pdf │ ├── final patent draft.docx │ ├── final testing report.docx │ ├── final synopsis.docx │ ├── final srs.doc │ ├── FIRST SECTION.pdf │ ├── SECOND SECTION.pdf │ ├── THIRD SECTION.pdf │ ├── MAJOR PROJECT PRESENTATION.pdf │ ├── 2 nd report merged.pdf │ ├── 3rd report merged.pdf │ └── submission rejection mail.png │ └── README.md
This structure demonstrates a complete production-grade implementation:
- AttedenceUpdate — Web application, admin panel, database, UI, and API endpoints.
- Admin — Full CRUD lifecycle for students, teachers, subjects, classes, and attendance.
- Bootstrap Layer — Enterprise-grade UI styling and responsive dashboard framework.
- RFID Integration — RfidResponse.php and submit-attendence-for-python.php act as real-time hardware ingestion bridges.
- AI Engine — Python OpenCV-based face detection, recognition, training, and attendance marking.
- DOCUMENTS — Compliance-grade research papers, final reports, patents, SRS, testing, and submission artifacts.
- Open PHP dashboard
- Start Python recognition
- Scan RFID and appear before camera
- Observe instant attendance mark
This platform provides a compliant, auditable, and highly reliable attendance automation solution. Its dual-factor identity model, modular architecture, and enterprise-grade backend make it suitable for regulated and high-trust environments while remaining extensible for future innovation.