Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome Lists | Featured Topics | Projects

https://github.com/usamafayaz/industrial-watch-backend

Industrial Watch is an AI-based system that enhances workplace efficiency and product quality in industrial settings. It uses AI technologies to monitor employee performance, detecting cigarette use, mobile phone use, and improper posture, as well as identifying defects in products like centrifugal discs, water bottles, and textiles.
https://github.com/usamafayaz/industrial-watch-backend

artificial-intelligence automation image-processing machine-learning mediapipe video-processing yolov8

Last synced: 2 months ago
JSON representation

Host: GitHub
URL: https://github.com/usamafayaz/industrial-watch-backend
Owner: usamafayaz
Created: 2024-04-03T09:50:42.000Z (10 months ago)
Default Branch: master
Last Pushed: 2024-10-30T11:55:31.000Z (3 months ago)
Last Synced: 2024-11-13T00:13:44.299Z (2 months ago)
Topics: artificial-intelligence, automation, image-processing, machine-learning, mediapipe, video-processing, yolov8
Language: Python
Homepage:
Size: 112 MB
Stars: 4
Watchers: 3
Forks: 0
Open Issues: 0
Metadata Files:
- Readme: README.md

Awesome Lists containing this project

README

# Industrial Watch Backend

## Overview
Industrial Watch is a comprehensive AI-based monitoring system designed to enhance workplace efficiency and product quality in industrial settings. This project employs advanced AI technologies to monitor employee performance and detect defective products, ensuring compliance with workplace rules and maintaining high standards of production quality.

## Features

### Employee Performance Monitoring
Our system leverages AI camera monitoring to track and evaluate employee activities based on specific rules and criteria:

- **Cigarette Detection**: Monitors and detects smoking within the workplace. Violations are logged, and fines are imposed based on predefined rules.
- **Mobile Usage Detection**: Identifies unauthorized mobile phone usage during working hours. Incidents are recorded, and penalties are applied according to the established regulations.
- **Posture Detection**: Ensures employees are adhering to posture guidelines. Any breaches are documented, and appropriate fines are administered.

Each of these modules operates with distinct rules and fine structures to ensure compliance and promote a disciplined working environment.

### Defective Product Detection
Our AI models are trained to identify defects in various products, ensuring only high-quality items proceed through the production line. The modules include:

- **Centrifugal Discs**: Detects imperfections and anomalies in centrifugal discs, ensuring they meet the required standards.
- **Water Bottles**: Monitors water bottles for defects such as missing cap or label, maintaining product integrity.
- **Textile Defects**: Identifies issues in textile products, such as thread inconsistencies, and fabric damage.

## Technology Stack
- **Backend**: Python
- **AI Models**: YOLOv8, PyTorch
- **Database**: SQL Server
## Front-end Integration
This project is a group effort with multiple front-end implementations to ensure compatibility across various platforms. The front-ends are developed using:
- **Android**: Native Android application.
- **React Native**: For seamless mobile application interface.
- **Flutter**: Cross-platform mobile application.
- **iOS**: Native iOS application.
## Installation and Setup

1. Clone the repository:
```bash
git clone https://github.com/usamafayaz/industrial-watch-backend.git
```

2. Navigate to the project directory:
```bash
cd industrial-watch-backend
```

3. Install Python dependencies:
```bash
pip install -r requirements.txt
```

4. Configure environment variables:
- Create a `.env` file and add the necessary configurations.

5. Start the server:
```bash
python app.py
```

## Contact
For any inquiries or support, please contact [[email protected]] or [[email protected]].