IndustrialWatch is an AI-powered monitoring system designed to enhance workplace efficiency and product quality in industrial settings. This project integrates advanced AI technologies to monitor employee performance and detect defective products, promoting compliance with workplace rules and maintaining high production standards.

The system leverages AI camera monitoring to track and evaluate employee activities based on specific rules:

• Cigarette Detection: Monitors smoking in the workplace, logging violations and imposing fines.
• Mobile Usage Detection: Identifies unauthorized mobile phone use during work hours, enforcing penalties.
• Posture Detection: Ensures proper posture by detecting incorrect sitting positions and issuing alerts.

AI models are trained to identify defects in various products:

• Centrifugal Discs: Detects anomalies to ensure product quality.
• Water Bottles: Monitors for defects such as missing caps or labels to maintain product integrity.
• Textile Defects: Identifies weaving faults and fabric damage in textile products.

The project includes a frontend developed in Android Native, offering a user-friendly mobile application.

• Backend: Python
• AI Models: YOLOv8, PyTorch
• Database: SQL Server

1. Clone the repository:

   git clone https://github.com/abimonyo/IndustrialWatch.git

2. Navigate to the project directory:

   cd IndustrialWatch

3. For the backend server:

    git clone https://github.com/abimonyo/IndustrialWatch.git

For any inquiries, please contact [[email protected]].