ESP32 Fingerprint Attendance System with Live Web Dashboard

Biometric attendance system uses ESP32 with AS608 optical fingerprint sensor to record attendance. When a registered finger is placed on the sensor, it identifies the person and logs entry with timestamp to a web dashboard. Stores up to 127 fingerprint templates. Admin features: enroll via serial command, delete by ID, clear all. Dashboard shows today's attendance, export CSV, search by name. Data sent to Google Sheets via HTTP GET to Apps Script webhook. Telegram Bot notifications on enroll or attendance mark. LCD 16x2 shows status. Libraries: Adafruit Fingerprint Sensor, WiFi, LiquidCrystal I2C, UniversalTelegramBot, ArduinoJson. Circuit: AS608 TX->GPIO16, RX->GPIO17.

Detailed Project Description

ESP32 Fingerprint Attendance System with Live Web Dashboard 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: dual-core Wi-Fi + Bluetooth microcontroller that runs the firmware, reads the sensors and hosts the network connection.
- 16x2 LCD (I2C): character display used for local readout.
- Fingerprint sensor (R307/R503): optical/capacitive sensor that enrols and verifies fingerprints over UART.
- Buzzer: audible alert output.
- Telegram Bot API: messaging channel used to send alerts and receive commands.
- Google Sheets: spreadsheet used as a cloud data log via Apps Script.

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, Adafruit Fingerprint Library, Google Apps Script 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