This project is an AIoT application built with Next.js, FastAPI, and the ESP32-S3. It provides a web service that allows you to control your devices, perform Over-the-Air (OTA) updates, and deploy or switch AI models. Currently, it only supports Object Detection models.

• Remote Device Control: Manage and interact with your ESP32-S3 devices directly from the web interface.
• OTA Updates: Seamlessly update the firmware of your devices over the air.
• AI Model Management: Deploy and switch between different object detection models on your devices.

The core of this project relies on the WebSocket protocol to establish real-time communication between the frontend (web interface), the backend (server), and the device (ESP32-S3). A task management system is implemented to synchronize the state between the backend and the device, ensuring reliable command execution and status updates.

This is the first version (v1) of the project. As it is developed and maintained by a single student, there might be some bugs. Please be patient, as bug fixes may be slower than in commercially developed software. Your understanding and contributions are highly appreciated!

The next major release will focus on enhancing the project's robustness, security, and functionality. Here are the planned features for v2:

• MQTT for Task Publishing: Transition the task publishing protocol from WebSocket to MQTT for more reliable and scalable messaging.
• QR Code Provisioning: Add a feature to configure device Wi-Fi credentials by scanning a QR code, simplifying the setup process.
• TLS Encryption: Implement Transport Layer Security (TLS) to secure the communication channels between all components.
• Image Classification Support: Extend AI model support to include image classification models.

1. Clone the repository: git clone https://github.com/boxain/aiot_web.git cd your-project

2. Create your environment files:

   • copy backend/.env.example file to backend/.env
   • copy frontend/.env.example file to frontend/.env.local

3. Modify the values in .env and .env.local to suit your needs.

4. Build and run the application: docker compose up --build -d