Category: Industry Defined Problem | Organization: Jyoti CNC Automation, Rajkot
This project integrates AI-powered Personal Protective Equipment (PPE) detection and CCTV-based Anomaly Surveillance into a single real-time system. It is designed to improve Workplace Safety, Regulatory Compliance, and Operational Efficiency in industrial environments.
Using advanced Deep Learning models and Computer Vision, the system ensures that workers adhere to safety protocols and that unusual or unsafe activities are promptly flagged.
- Real-time detection of:
- 🪖 Helmets
- 😷 Face Masks
- 👷 Safety Vests
- 🧤 Gloves
- Supports live feed from Webcam/IP Camera
- Upload and analyze Video/Image files
- Detection logs with timestamps and confidence scores
- Real-time detection of:
- 🚫 Entry into restricted zones
⚠️ Safety violations (e.g., no helmet, improper behavior)- 🚷 Suspicious or unsafe movements
- Continuous monitoring via CCTV/IP camera
- Alert generation on detection
- Live status feed with detection results
- Real-time preview of camera feed
- Violation and compliance logs
- Summary statistics and compliance reports
| Component | Technology |
|---|---|
| 💡 AI Model | YOLOv8 (Ultralytics) |
| 🧠 Backend | Python, OpenCV |
| 🌐 Frontend/UI | Streamlit |
| 🎥 Video Input | Webcam/IP Camera |
| 📊 Data Logging | Pandas, CSV Logs |
- ✅ Automated compliance with PPE policies
- 🔍 Real-time safety monitoring
- 📉 Reduced accident risk and manual supervision
- 📊 Actionable insights from safety data
- 📷 Detected image with PPE boxes
- 🧾 Logs with timestamp and violation type
- 📈 Streamlit dashboard with real-time updates
# 1. Clone the repository
git clone https://github.com/darshan1654/AI-PPE-Detection.git
# 2. Create and activate a virtual environment
python -m venv venv
source venv/bin/activate # or venv\Scripts\activate on Windows
# 3. Install required dependencies
pip install -r requirements.txt
# 4. Run the application
streamlit run app.py├── app.py # Streamlit app
├── best.pt # YOLOv8 model files
├── yolov8n.pt # YOLOv8 model files
├── violation_logs.csv # Detection logs CSV file
├── requirements.txt # Dependencies
├── packages.txt # packages
└── runtime.txt # For deployment (e.g., Heroku)
Group ID: G00171
| Name | |
|---|---|
| Kushal A. Parekh | 22ce113@svitvasad.ac.in |
| Darshan Pardeshi | darshanpardeshi1654@gmail.com |
| Param V. Jani | janiparam61@gmail.com |
| Darshan Panchal | mpdarshanpanchal001031@gmail.com |
| Jaymin Raval | ravaljaymin2908@gmail.com |
- 🔔 Voice/Email/SMS alert system
- 🔗 Integration with ERP systems
- 📊 Admin dashboard with analytics
- 📤 Auto-upload violation clips
- 📡 Multi-location camera support
- ✅ Used in Real Industrial setup at Jyoti CNC
- 🎓 Presented at College-level expo
- 📡 Successfully tested with Live Camera feeds
For Academic and Research use only.
- Ultralytics YOLOv8
- OpenCV
- Streamlit
- Jyoti CNC Automation Pvt. Ltd.
- SVIT Vasad
📧 janiparam61@gmail.com 📧 darshanpardeshi1654@gmail.com 📧 22ce113@svitvasad.ac.in 📧 mpdarshanpanchal001031@gmail.com 📧 ravaljaymin2908@gmail.com
