Smart Elevator Optimization System Using Real-Time Monitoring and Machine Learning

Table of Contents

• Project Overview
• Technologies Used
• Installation
• Usage
• Features
• How It Works
• Contributing
• License

Project Overview

The Smart Elevator Optimization System is designed to optimize elevator operations by integrating real-time monitoring and machine learning. The system uses computer vision techniques to detect people in and around elevators, ensuring efficient stopping and usage.

Technologies Used

• Programming Language: Python
• Frameworks:
  • Streamlit for the frontend interface
  • TensorFlow for the object detection model
• Libraries:
  • OpenCV for image processing
  • NumPy for numerical computations
  • PIL for image handling

Installation

To set up the project locally, follow these steps:

1. Clone the repository:

   git clone https://github.com/yourusername/smart-elevator-optimization.git
   cd smart-elevator-optimization