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Employee Productivity Monitoring System

This project aims to use facial recognition technology to monitor employee productivity and track specific activities in the workplace.

You can visit the SSL encrypted website hosted on AWS https://www.cwem.site/

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Features

  • Detects whether the right person is sitting in front of the camera
  • Tracks key points on the face (such as eyes, mouth) to identify specific activities
  • Classifies the type of activity the user is performing (e.g. taking a phone call, looking away from the screen, sleeping, looking tired)
  • Lightweight and runs in the browser
  • Sends summary data about activities to a central server in JSON format, without transmitting any images or videos
  • Automatic Database Records: The system automatically adds records of employee activities to the database, eliminating the need for manual data entry. This ensures accurate and up-to-date tracking of employee actions and enables comprehensive reporting and analysis of productivity metrics.

Requirements

  • A computer with a webcam
  • A modern web browser (such as Chrome or Firefox)

Installation

Option 1: Local Installation

  1. Clone this repository to your local machine
  2. Install the necessary dependencies by running pip install -r requirements.txt
  3. Run the app by executing python app.py
  4. Open your web browser and navigate to http://localhost:8080

Option 2: GitHub Codespaces

  1. Open the project in GitHub Codespaces.
  2. Update the apt package manager and install FFmpeg:
  3. sudo apt update sudo apt-get install ffmpeg
  4. Install the necessary dependencies by running pip install -r requirements.txt
  5. Run the application by executing python app.py
  6. Open your web browser and navigate to http://localhost:8080

Technologies Used

Privacy

We take the privacy of our employees seriously. No images or videos of users are transmitted to the central server - only summary data about their activities is sent. All data is handled in accordance with relevant privacy laws and regulations.

Documentations