Integrating Seeed XIAO ESP32S3 Sense with Home Assistant opens up a realm of possibilities for home monitoring and automation. This project not only establishes a seamless connection between the two but also enhances surveillance capabilities with automatic pet recognition. By deploying this solution, users can monitor designated areas, receive instant alerts on pet intrusion, and even trigger actions to deter pets from restricted zones.
The Seeed Studio XIAO Thumb-sized Development Board, equipped with a camera sensor, digital microphone, and SD card support, serves as the foundation of this project. Its advanced features, including a detachable OV2640 camera sensor, lithium battery charging management, and extensive connectivity options, make it an ideal choice for intelligent AI applications.
This project comprises three main components: the IoT central platform (Home Assistant deployed on a Raspberry Pi), Seeed Studio XIAO Sense, and AI image recognition powered by Yolov8. The Raspberry Pi hosts services such as Home Assistant, ESPhome, and Mosquitto MQTT broker, all encapsulated within Docker containers for scalability and conflict-free operation.
How to do it:
- Setting up Docker services on Raspberry Pi: Install Docker and configure docker-compose.yml to deploy Home Assistant, ESPhome, and Mosquitto MQTT broker.
- Configuring ESPhome on Seeed XIAO ESP32S3 Sense: Flash firmware, configure settings via ESPhome interface, and upload device-specific code to enable camera functionality.
- Configuring Yolov8 on Raspberry Pi and integrating with Home Assistant for mobile alerts: Set up MQTT communication, create Python script for image recognition, and configure Home Assistant automation for push notifications.
Demonstration:
The project enables real-time pet detection and sends push notifications to the user's phone, ensuring prompt awareness of any intrusions. Further customization options, such as integrating peripherals to deter pets, are possible with additional automation configuration.
Exploring the fusion of Python, MQTT, and Home Assistant has expanded the horizons of home automation. This project underscores the potential of interconnected devices to create a truly smart home ecosystem, facilitating seamless communication and interoperability across various functionalities.
For more explanation and source code, please read the original project from Hackster.io
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