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$10 DIY AI Surveillance Camera With Motion Detection | Full Tutorial | Coders Cafe
Coders Cafe
Overview
This video tutorial demonstrates how to build a DIY AI surveillance camera using an ESP32 CAM board for under $10. The project integrates motion detection directly into the camera, eliminating the need for separate sensors. Upon detecting motion, the camera sends notifications to a Telegram account and captures short video footages accessible via a web dashboard from anywhere globally. The tutorial covers hardware component selection, software setup including Arduino IDE configuration and library installation, and the process of connecting the ESP32 CAM to a web service for remote monitoring and alerts. Finally, it shows how to assemble the camera into a 3D-printed case and test its functionality.
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Chapters
- The project involves building a low-cost surveillance camera using an ESP32 CAM board and a 3D-printed case.
- Motion detection is performed by the camera itself, triggering notifications to Telegram.
- A web dashboard allows viewing motion-detected footage remotely from anywhere in the world.
- The entire system can be built for under $10.
This chapter introduces a practical and affordable project that leverages AI for security, making advanced features accessible to hobbyists and DIY enthusiasts.
The camera is housed in a 'cute 3D printed case' that allows for adjustable angles.
- Essential hardware includes the ESP32 CAM board, an FTDI programmer for uploading code (as the ESP32 CAM lacks a USB port), jumper wires, a power adapter, and 3D-printed parts.
- Software setup requires the Arduino IDE.
- The ESP32 add-on needs to be installed in the Arduino IDE to recognize ESP32 boards.
- Specific libraries must be installed: Elegant Surveillance, Telegram Bot, and ArduinoJson.
Understanding the necessary components and software is crucial for successfully replicating the project and troubleshooting any setup issues.
To upload code, the ESP32 CAM must be connected to a computer via an FTDI programmer, with a jumper connecting the 'GPIO0' pin to 'GND' to enable programming mode.
- A web dashboard service (motion.like.arduino.com) is used to manage the device and view footage.
- Users need to create an account and register a new device on the dashboard.
- A Telegram bot must be created using the 'BotFather' to receive motion alerts.
- The bot provides a 'user token' and 'device ID' for integration with the dashboard and code.
- A separate bot is used to obtain the Telegram chat ID for the bot.
This chapter explains how to connect the physical device to a cloud service and a messaging app, enabling remote monitoring and notifications.
After creating a bot with BotFather, you send the '/getid' command to the 'ID Bot' to retrieve your unique Telegram chat ID.
- The provided Arduino sketch needs to be modified with your Wi-Fi network's SSID and password.
- Input the 'user token' and 'device ID' obtained from the web dashboard into the code.
- Enter the 'bot token' and 'chat ID' obtained from the Telegram bot setup.
- Upload the configured code to the ESP32 CAM using the FTDI programmer, ensuring the GPIO0 to GND jumper is in place.
- After uploading, remove the GPIO0 jumper and reconnect the USB to power the board for normal operation.
Correctly configuring and uploading the code is the final step to integrate all hardware and software components, making the camera functional.
The code requires specific placeholders for 'ssid', 'password', 'user_token', 'device_id', 'bot_token', and 'chat_id' which must be filled with your personal credentials.
- Power on the ESP32 CAM after uploading the code.
- Test motion detection by moving your hand in front of the camera.
- Verify that a notification is received on Telegram and that footage appears on the web dashboard.
- Assemble the ESP32 CAM into the 3D-printed case for a finished, deployable unit.
- The 3D-printed parts also include provisions for powering the ESP32 CAM.
This chapter confirms the project's success and demonstrates how to finalize the build for practical use.
Upon detecting motion, a notification appears on the Telegram app, and a short video clip of the event is available on the web dashboard.
Key takeaways
- The ESP32 CAM is a versatile and inexpensive microcontroller ideal for DIY IoT projects involving cameras.
- Motion detection can be implemented directly on the microcontroller using camera input, bypassing the need for separate hardware sensors.
- Integrating with services like Telegram and custom web dashboards enables powerful remote monitoring and notification capabilities.
- Proper setup of the Arduino IDE, including board support and libraries, is essential for programming ESP32 devices.
- Understanding the role of specific pins (like GPIO0 for programming mode) and connection requirements (like using an FTDI programmer) is critical for hardware interaction.
- Low-cost components can be combined to create sophisticated AI-powered devices, democratizing access to smart technology.
- The project demonstrates a practical application of embedded systems, cloud connectivity, and mobile notifications.
Key terms
ESP32 CAMFTDI ProgrammerMotion DetectionTelegram BotWeb DashboardArduino IDEGPIO0SSIDUser TokenDevice ID
Test your understanding
- What is the primary advantage of using the ESP32 CAM for this project compared to other microcontrollers?
- How does the ESP32 CAM perform motion detection without a dedicated motion sensor?
- What are the essential steps to set up the Telegram notification system for the surveillance camera?
- Why is an FTDI programmer necessary for programming the ESP32 CAM?
- How can you verify that the DIY surveillance camera is functioning correctly after uploading the code?