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AI and digital twin-Driven Smart Building Facilities Management

Project Overview

This project focuses on implementing a AI and Digital twin-driven decision support system for for smart building facilities management using digital twins, and large language models (LLMs). The aim is to enhance facility management through AI-driven insights and digital twin visualizations.

Key Features

  • Digital Twin Visualization: Creates a virtual replica of building systems to provide real-time monitoring and decision support.
  • Large Language Models (LLMs): Incorporates LLMs for advanced data analysis and natural language processing to improve governance and operational efficiency.
  • AI-Driven Insights: Provides actionable insights through AI and data analytics to optimize building management and operations.

Video Demo

Watch the demo video
Click on the image to view the video.

Requirements

  • Open-source Large language model (e.g., LLaMA)
  • Groq API
  • Generative AI inference tool. llama.cpp
  • Python 3.10
  • Raspberry Pi and IoT sensors

Detailed setup guide

Coming soon.....

License

This project is licensed under the MIT License.

Manuscript

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