Real-Time MQTT Monitoring and AI Analysis Workflow

This n8n workflow is designed to monitor MQTT topics in real-time, process incoming messages through AI-powered analysis, and store or log valuable insights automatically.

The workflow begins with a webhook that triggers when a new MQTT message is received on a specific topic. The message content is then split into manageable chunks using a Text Splitter node. These chunks are further processed by OpenAI’s embedding model to generate vector representations for semantic understanding.

The vectors are stored in a Redis database for efficient retrieval. When needed, the workflow can query this vector store to find relevant past messages or similar data points.

Using LangChain’s language models, the workflow can perform various tasks such as defining, summarizing, or analyzing the data. An agent orchestrates these language model interactions, leveraging memory buffers for context management.

Finally, the results are logged into a Google Sheet for record-keeping and further analysis. This workflow is highly suited for scenarios like IoT device monitoring, intelligent data analysis, or automated logging of MQTT message streams, providing a seamless integration of MQTT, AI, and data storage tools.