Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/codecrood/smart-iot-world
CodeCrood develops innovative IoT systems combining web and mobile UI with Node.js servers and NodeMCU (ESP8266). We focus on enabling seamless interaction, real-time monitoring, and efficient automation across diverse applications.
https://github.com/codecrood/smart-iot-world
esp8266 internet-of-things node-js react
Last synced: about 1 month ago
JSON representation
CodeCrood develops innovative IoT systems combining web and mobile UI with Node.js servers and NodeMCU (ESP8266). We focus on enabling seamless interaction, real-time monitoring, and efficient automation across diverse applications.
- Host: GitHub
- URL: https://github.com/codecrood/smart-iot-world
- Owner: CodeCrood
- Created: 2024-11-25T15:13:09.000Z (about 2 months ago)
- Default Branch: main
- Last Pushed: 2024-11-25T18:33:12.000Z (about 2 months ago)
- Last Synced: 2024-11-25T18:36:44.344Z (about 2 months ago)
- Topics: esp8266, internet-of-things, node-js, react
- Language: JavaScript
- Homepage:
- Size: 17.6 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Smart IoT World
Welcome to **Smart IoT World** – a repository for various **IoT projects** developed by **CodeCrood**. This repository aims to build and deploy **smart automation solutions** using multiple platforms, including **React** for frontend user interfaces, **Node.js** for server-side logic, **NodeMCU (ESP8266)** for sensor and actuator control, and **Raspberry Pi** for machine learning applications.
Each project in this repository focuses on different aspects of IoT systems, allowing for a variety of use cases, from smart home automation to machine learning-based predictions and controls.
## Project Structure
The repository follows a modular structure where each project consists of the following components:
- **Frontend (React)**: The user interface (UI) is built using React for both web and mobile applications, providing an interactive and responsive experience for controlling IoT devices.
- **Backend (Node.js)**: The backend server handles HTTP requests, processes data, and communicates with IoT devices.
- **Hardware (NodeMCU, Raspberry Pi, Sensors, Actuators)**: Various hardware platforms, including **NodeMCU (ESP8266)** for connecting sensors/actuators and **Raspberry Pi** for more advanced applications like machine learning.
- **Machine Learning**: Some projects leverage the power of **Raspberry Pi** to run machine learning algorithms for real-time predictions, anomaly detection, or other advanced tasks.
### Folder Structure
```bash
smart-iot-world/
├── HomeControlHub/ # Example Project 1
│ ├── backend/ # Node.js server for project 1
│ ├── frontend/ # React app for web and mobile UI
│ ├── hardware/ # NodeMCU firmware and hardware setup
└── README.md # This README file
```
## Technologies Used
- **React** for the frontend UI (both web and mobile).
- **Node.js** and **Express.js** for handling the server-side logic.
- **NodeMCU (ESP8266)** for controlling IoT sensors and actuators.
- **Raspberry Pi** for running machine learning models and processing data.
- **MQTT/HTTP** protocols for communication between devices and the server.
## Getting Started
Each project in this repository can be set up individually. Follow the specific instructions inside each project folder for detailed setup and configuration.
### Steps to Get Started
1. Clone the repository to your local machine:
```bash
git clone https://github.com/CodeCrood/smart-iot-world.git
cd smart-iot-world
```
2. Navigate to the desired project folder:
```bash
# or any other project folder
cd HomeControlHub
```
3. **Set Up Backend**:
- Navigate to the **`backend`** folder.
- Install dependencies and start the server:
```bash
cd backend
npm install
npm start
```
4. **Set Up Frontend**:
- Navigate to the **`frontend`** folder.
- Install dependencies and start the development server:
```bash
cd frontend
npm install
npm start
```
5. **Upload Firmware to Hardware**:
- For **NodeMCU**, upload the appropriate firmware (Arduino code) from the **`hardware`** folder.
- For **Raspberry Pi**, follow the instructions in the **`machine-learning`** folder to set up your Pi with the required libraries and models.
## Example Projects
1. **HomeControlHub**: Smart Light Control
- **Frontend**: React web app to control lights.
- **Backend**: Node.js API to update light status.
- **Hardware**: NodeMCU connected to a relay for controlling lights.
## Features
- **IoT Device Control**: Remotely control devices like lights, fans, and sensors.
- **Real-Time Data**: Get live updates and status from devices.
- **Machine Learning Integration**: Use Raspberry Pi to run ML models for predictive analytics.
- **Cross-Platform**: Web and mobile UI for all devices.
## Future Enhancements
- Integration of more IoT devices such as security cameras, HVAC systems, etc.
- Improved machine learning models for advanced use cases.
- Integration with cloud platforms for remote monitoring.
## License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
## Contributing
We welcome contributions to enhance the project! Feel free to fork the repository and submit pull requests.
---
**CodeCrood IoT Systems** is dedicated to creating smarter, more connected worlds through innovative IoT and machine learning applications.