ESP32 Real-Time Face Recognition Attendance System
Build a face recognition attendance system using ESP32-CAM that automatically logs attendance with timestamp to Firebase when a registered face is detected.
- Suitable forB.Tech AI students
- Build time5-7 weeks
- LevelAdvanced
- Available atAjvika Labs, Kakinada
About this project
AI-powered attendance system uses ESP32-CAM with built-in face detection and recognition to automatically record attendance. When a registered face detected in camera frame, system logs person name and timestamp to Firebase Realtime Database. Admin web interface: add/remove faces by capturing samples (10 photos from different angles), view attendance logs, export CSV report. ESP32-CAM runs built-in face detection (HumanFaceDetect.h) and face recognition (FaceRecognition.h from esp32-camera library). Face database stored in SPIFFS (up to 7 faces due to PSRAM limitation). Recognition confidence threshold configurable (default 0.85). LED indicator: green flash for recognized face, red for unknown. OLED shows recognized name and confidence score. Libraries: esp_camera, WiFi, SPIFFS, Firebase ESP Client, ArduinoJson. Ensure 5V 2A power supply for camera stability.
Detailed Project Description
ESP32 Real-Time Face Recognition Attendance System replaces manual registers with automatic, tamper-resistant attendance marking, storing every entry with a timestamp so reports can be generated instantly.
How It Works
1. Each user is enrolled once (card / fingerprint / face / login) and stored with an ID.
2. On arrival the system identifies the user, checks against the enrolled records and marks attendance with date and time.
3. Records are saved to a database and shown on a dashboard or exported as reports.
4. Duplicate or late entries are handled according to the configured rules.
Key Components and Their Role
- ESP32-CAM: ESP32 module with an OV2640 camera used to capture images or stream video.
- OLED display (SSD1306): 128x64 I2C display used to show live readings and status.
- Camera module: image sensor used for capture, streaming or computer vision.
- Firebase: Google cloud backend used for realtime database, auth and hosting.
Implementation Steps
1. Collect the components and study each module's datasheet (pin-out, voltage, interface).
2. Wire the circuit on a breadboard following the pin mapping; power sensors from the correct rail (3.3 V / 5 V).
3. Install Arduino IDE, Firebase ESP32 Client, ESP32 Camera Library and the required libraries; flash a minimal test sketch for each module separately.
4. Write the main firmware: read sensors → process → drive outputs / send data.
5. Configure network or cloud credentials and test communication end-to-end.
6. Calibrate thresholds, add error handling (reconnect, sensor time-out) and run a long-duration test.
7. Finalise on a PCB / enclosure and document wiring, code and results.
Key Features
- One-time enrolment
- Instant identification
- Timestamped records
- Daily / monthly reports
- Admin panel
Expected Output
On completion the student will have an attendance log with name, ID, date and time for every entry, plus summary reports.
Deliverables
- Complete source code with comments
- Circuit diagram and pin mapping
- Project report with screenshots and results
- Demonstration-ready build
Detailed Project Description
ESP32 Real-Time Face Recognition Attendance System replaces manual registers with automatic, tamper-resistant attendance marking, storing every entry with a timestamp so reports can be generated instantly.
How It Works
1. Each user is enrolled once (card / fingerprint / face / login) and stored with an ID.
2. On arrival the system identifies the user, checks against the enrolled records and marks attendance with date and time.
3. Records are saved to a database and shown on a dashboard or exported as reports.
4. Duplicate or late entries are handled according to the configured rules.
Key Components and Their Role
- ESP32-CAM: ESP32 module with an OV2640 camera used to capture images or stream video.
- OLED display (SSD1306): 128x64 I2C display used to show live readings and status.
- Camera module: image sensor used for capture, streaming or computer vision.
- Firebase: Google cloud backend used for realtime database, auth and hosting.
Implementation Steps
1. Collect the components and study each module's datasheet (pin-out, voltage, interface).
2. Wire the circuit on a breadboard following the pin mapping; power sensors from the correct rail (3.3 V / 5 V).
3. Install Arduino IDE, Firebase ESP32 Client, ESP32 Camera Library and the required libraries; flash a minimal test sketch for each module separately.
4. Write the main firmware: read sensors → process → drive outputs / send data.
5. Configure network or cloud credentials and test communication end-to-end.
6. Calibrate thresholds, add error handling (reconnect, sensor time-out) and run a long-duration test.
7. Finalise on a PCB / enclosure and document wiring, code and results.
Key Features
- One-time enrolment
- Instant identification
- Timestamped records
- Daily / monthly reports
- Admin panel
Expected Output
On completion the student will have an attendance log with name, ID, date and time for every entry, plus summary reports.
Deliverables
- Complete source code with comments
- Circuit diagram and pin mapping
- Project report with screenshots and results
- Demonstration-ready build
Technologies used
Hardware components
- ESP32-CAM Module
- FTDI Programmer
- OLED Display
- Green Red LEDs
- 5V 2A Power Supply
Software & tools
- Arduino IDE
- Firebase ESP32 Client
- ESP32 Camera Library
- ArduinoJson
What you get
- Working project / hardware kit, tested before delivery
- Complete source code with explanation
- Project demo and guidance for your viva
- Project report, PPT and IEEE paper support (on request)
Delivery & Payment
Delivery takes a minimum of two weeks from the date your inquiry is confirmed.
Payment is in two parts:
• 50% advance to start the project
• Remaining 50% before delivery
Note:
• Documentation and PPT are not included by default
• If you need documentation/PPT, it can be arranged for extra time and cost
We'll confirm the exact timeline and cost with you after reviewing your requirements.
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