• Author: Felicia Saghin
• Email: felicia.saghin@stud.acs.pub.ro
• Master: SRIC

In today’s connected world, real-time security monitoring at home or in small offices has become both practical and affordable. This project delivers a lightweight IoT door-security solution by combining an ESP32-CAM module with a Hall-effect sensor. Whenever the door opens, the sensor immediately signals the ESP32-CAM to capture a high-resolution image. That image is then uploaded to Firebase Storage, and its publicly accessible URL is written to Firebase Realtime Database. Simultaneously, Twilio’s API is invoked to send an SMS to your smartphone. Finally, a web gallery hosted on Firebase displays the latest snapshot instantly, giving you secure and remote visibility of every entry event.

Diagram In many homes and small offices, it’s hard to know in real time if someone has opened a door while you’re away. Traditional locks only log locally or require you to check in person. This project closes that gap by combining a Hall-effect sensor, an ESP32-CAM, cloud storage and instant SMS alerts.

Key features:

• Instant detection of door opening via a Hall-effect sensor mounted on the door frame
• Automated photo capture by ESP32-CAM when the sensor toggles
• Cloud storage of each snapshot in Firebase Storage
• Real-time SMS notifications via Twilio with a link to the gallery
• Live web monitoring through a Firebase-hosted photo gallery

When the door swings open, the Hall sensor’s output changes state. The ESP32-CAM immediately takes a JPEG, uploads it to Firebase Storage, and writes it into Realtime Database. A Twilio API call then sends you an SMS alert containing the gallery URL. Meanwhile, your web app—hosted on Firebase Hosting and listening to the database—updates instantly to show the new image.

Hardware Circuit

Connecting Components

Hall-effect Sensor (A3144) Mounted on the door frame. Detects the magnet fixed to the door as it swings past: output goes LOW when the magnet is within 5–10 mm (door closed), and HIGH when it moves away (door open).

• VCC → ESP32-CAM 3V3
• GND → ESP32-CAM GND
• OUT → ESP32-CAM GPIO13 (`INPUT_PULLUP`)

ESP32-CAM Module Handles image capture, Firebase upload, and Twilio notifications.

• Power → VIN pin → +5 V from your battery pack (e.g. USB power-bank or Li-Po + boost converter)
• Ground → GND → battery pack GND
• (If you’re using the ESP32-CAM-MB shield instead of wiring VIN/GND, just plug your battery’s USB cable into its micro-USB port.)*

USB-Serial Adapter *(only if not using the on-board USB shield)* Required to flash code to the ESP32-CAM.

• Adapter TX → ESP32-CAM U0R0 (GPIO3)
• Adapter RX → ESP32-CAM U0T0 (GPIO1)
• Adapter +5 V → ESP32-CAM VIN
• Adapter GND → ESP32-CAM GND

Permanent Magnet Mounted on the door so its north pole passes within 5–10 mm of the Hall sensor when the door is closed. No wiring required.

<note tip>I used VS Code with the PlatformIO IDE extension. I’ve built the core logic so that each door-open triggers exactly one clean sequence:

• A debounce routine on the Hall sensor waits for the input to remain stable (no rapid bouncing) for ~50 ms before recognizing a genuine open event.

• I track the previous sensor state to detect a rising edge (closed→open) and ignore all other transitions.

• On that single edge, the ESP32-CAM captures a JPEG, then immediately:

• * Uploads it to Firebase Storage over HTTPS.

• * Parses the JSON response to extract the download URL.

• * Writes that into Firebase Realtime Database.

• * Calls Twilio’s REST API (over secure TLS) to send an SMS with the gallery link.

After each step I check for errors and retry once if something fails (network hiccup, JSON parse error, etc.).

Finally, I release the camera buffer and reset state, so the loop stays non-blocking (using millis() for timing) and immediately resumes listening for the next door-open.

All of this makes the system rock-solid: one photo, one upload, one DB update, one SMS—every single time.