Welcome to my Node-RED IoT Temperature Prediction Project repository! 🌐

The Node-RED IoT Temperature Prediction Project is an innovative solution for predicting temperatures based on time-series data. Leveraging Node-RED, this project takes a CSV input of time and temperature, performs regression analysis, and predicts the temperature for the next minute. The results are visualized in a chart on the Node-RED dashboard.

• CSV Input Processing: Upload a CSV file containing time and temperature data to initiate the prediction process.
• Regression Analysis: Utilizes machine learning algorithms to perform regression on the input data for temperature prediction.
• Real-time Visualization: The predicted temperatures are dynamically displayed in a chart on the Node-RED dashboard.
• User-friendly Interface: Built with Node-RED, ensuring an intuitive and user-friendly experience for configuring and visualizing predictions.

Using the Node-RED IoT Temperature Prediction Project is straightforward:

1. Install Node-RED on your system if you haven't already. Node-RED Installation Guide
2. Clone or download this project repository to your local machine.
3. Import the Node-RED flow from the provided JSON file (iot_temp_regression.json) into your Node-RED instance.
4. Deploy the Node-RED flow and open the Node-RED dashboard.
5. Choose a CSV file with time and temperature data using the designated file node, or any other input series.
6. Witness real-time temperature predictions displayed on the dashboard chart.

We encourage contributions to enhance the Node-RED IoT Temperature Prediction Project! Here's how you can get involved:

• Fork the repository and make your desired changes.
• Submit a pull request with a detailed explanation of the enhancements you've made.
• Engage in discussions with other contributors to exchange ideas and collaborate on future improvements.

• Node-RED: A flow-based development tool for visual programming.

I appreciate your support. Happy coding! 📈🌐