Calculate Embodied Carbon (CO2) for Revit/IFC Models using AI Classification

# n8n Workflow: AI-Powered Carbon Footprint Calculation for Revit Models

This n8n workflow demonstrates a robust process for calculating the embodied carbon (CO2) for Revit models, leveraging AI classification, data processing, and local file operations. It's designed to automate the extraction, classification, and calculation of carbon data from a spreadsheet, providing a structured output.

## What it does

This workflow automates the following steps:

1.  **Manual Trigger**: Initiates the workflow upon a manual click, allowing for on-demand execution.
2.  **Read Binary File**: Reads a binary file, likely a spreadsheet containing Revit model data or material lists.
3.  **Spreadsheet File Conversion**: Converts the binary file into a structured spreadsheet format for easier processing.
4.  **Loop Over Items**: Iterates through each item (row) in the processed spreadsheet data.
5.  **AI Agent (Classification)**: For each item, an AI agent (configured to use either OpenAI, Anthropic, or xAI Grok Chat Models) is employed. This agent is likely responsible for classifying materials or components within the Revit model data to determine their carbon impact.
    *   **Anthropic Chat Model**: An alternative AI model for classification.
    *   **OpenAI Chat Model**: Another alternative AI model for classification.
    *   **xAI Grok Chat Model**: A third alternative AI model for classification.
6.  **Edit Fields (Set)**: Modifies or adds new fields to the data, potentially enriching it with AI classification results or preparing it for carbon calculation.
7.  **If Condition**: Evaluates a condition based on the processed data (e.g., checking if the AI classification was successful or if specific data points exist).
8.  **Execute Command (True Branch)**: If the condition is true, a shell command is executed. This could be for running a local script to perform carbon calculations, interact with a local database, or trigger another system.
9.  **Code (False Branch)**: If the condition is false, a custom JavaScript code snippet is executed. This might handle error logging, default values, or alternative processing.
10. **Merge**: Combines the data streams from both the "If" node's true and false branches, ensuring all processed items are rejoined.
11. **Write Binary File**: Writes the final processed data (potentially including calculated carbon footprints) back to a binary file, likely a new spreadsheet or a report.

## Prerequisites/Requirements

To use this workflow, you will need:

*   **n8n Instance**: A running n8n instance.
*   **AI Service Credentials**:
    *   An **OpenAI API Key** (if using the OpenAI Chat Model or OpenAI Agent).
    *   An **Anthropic API Key** (if using the Anthropic Chat Model).
    *   An **xAI Grok API Key** (if using the xAI Grok Chat Model).
*   **Local System Access**: The n8n instance needs permissions to execute shell commands (`Execute Command` node) and read/write binary files (`Read Binary File`, `Write Binary File` nodes) on the host system.
*   **Input Spreadsheet**: A spreadsheet file containing the Revit model data (e.g., material lists, quantities, component types) that needs to be processed.
*   **Carbon Calculation Logic/Script**: Any external scripts or tools that the `Execute Command` node will call to perform the actual embodied carbon calculations based on the AI-classified data.

## Setup/Usage

1.  **Import the workflow**: Download the JSON provided and import it into your n8n instance.
2.  **Configure Credentials**:
    *   For the `AI Agent`, `Anthropic Chat Model`, `OpenAI Chat Model`, and `xAI Grok Chat Model` nodes, configure your respective API credentials.
3.  **Specify File Paths**:
    *   In the `Read Binary File` node, specify the full path to your input Revit model data spreadsheet.
    *   In the `Write Binary File` node, specify the desired output path and filename for the processed carbon footprint report.
4.  **Customize AI Agent**: Adjust the prompt and configuration of the `AI Agent` node to accurately classify your Revit model components based on your specific data and desired carbon categories. You may choose between OpenAI, Anthropic, or xAI Grok models within the AI Agent configuration.
5.  **Customize `Execute Command`**: If you have a custom script for carbon calculation, update the `Execute Command` node with the appropriate command and arguments to run your script, passing the necessary data from the workflow.
6.  **Review `Code` Node**: If the "If" condition leads to the `Code` node, ensure its JavaScript logic aligns with your error handling or alternative processing requirements.
7.  **Execute Workflow**: Click "Execute Workflow" in the `Manual Trigger` node to run the process.

This workflow provides a powerful framework for integrating AI classification into environmental impact assessments for architectural and construction projects, streamlining the calculation of embodied carbon for Revit models.