Unlock Location Intelligence with BLE Beacon Mapper
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The BLE Beacon Mapper workflow automates the processing and analysis of Bluetooth Low Energy (BLE) beacon data. It leverages AI to ingest, embed, and query location information, transforming raw beacon signals into actionable insights.
About This Workflow
The BLE Beacon Mapper is a powerful n8n workflow designed to harness the potential of Bluetooth Low Energy (BLE) beacons for advanced location tracking and data analysis. This workflow ingests real-time beacon data via a webhook, intelligently splits and embeds this information using Hugging Face embeddings, and stores it in a Pinecone vector database. It then enables intelligent querying and agent-based interaction, allowing for dynamic analysis of beacon proximity and data. Finally, all interactions and processed data are logged to a Google Sheet for comprehensive record-keeping and further analysis, providing a complete solution for IoT location intelligence.
Key Features
- Real-time Data Ingestion: Seamlessly captures BLE beacon data through a configurable webhook.
- AI-Powered Embedding: Utilizes Hugging Face embeddings to represent beacon data semantically.
- Scalable Vector Storage: Leverages Pinecone for efficient storage and retrieval of location data.
- Intelligent Querying & Agents: Enables natural language querying and AI-driven analysis of beacon information.
- Automated Logging: Logs all processed data and interactions to a Google Sheet for easy review.
How To Use
- Webhook Setup: Configure the
Webhooknode to receive incoming BLE beacon data via a POST request to the/ble_beacon_mapperendpoint. - Text Splitting: The
Splitternode automatically chunks incoming text data into manageable segments for processing. - Embedding Generation: The
Embeddingsnode uses Hugging Face models to create vector representations of the text chunks. - Data Insertion: Use the
Insertnode to store these embeddings in your Pinecone index namedble_beacon_mapper. - Data Querying: The
Querynode allows you to retrieve relevant information from the Pinecone index based on input queries. - AI Agent Configuration: Connect the
Tool(Pinecone Vector Store),Memory(Buffer Window), andChat(OpenAI) nodes to build an intelligent agent capable of understanding and responding to queries about beacon data. - Agent Execution: The
Agentnode orchestrates the interaction between the tools, memory, and chat model. - Logging: Configure the
Sheetnode with your Google Sheets credentials andSHEET_IDto log all agent outputs and relevant data to a 'Log' sheet.
Apps Used
Workflow JSON
{
"id": "2e2e50be-fde5-4925-85fe-e9b1c30b8752",
"name": "Unlock Location Intelligence with BLE Beacon Mapper",
"nodes": 7,
"category": "Marketing",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
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ID: 2e2e50be-fde5...
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