🛡️ Smart Safety Monitor

An AI-Powered Workplace Safety Monitoring System using Python, OpenCV, YOLOv8 and Tkinter Dashboard

Smart Safety Monitor is a modular Computer Vision application designed to improve workplace safety through real-time AI-powered surveillance.

The system continuously monitors live camera feeds and detects workplace safety violations using multiple YOLOv8 models.

It supports:

👤 Person Detection
📱 Mobile Phone Detection
🪖 Helmet Detection
🚫 No Helmet Detection
🦺 Safety Vest Detection
🔫 Weapon Detection

Whenever a violation occurs, the application automatically:

📸 Captures screenshots
📝 Logs events into CSV
📊 Updates Dashboard Analytics
⚡ Prevents duplicate alerts
📈 Displays live monitoring statistics

The project follows a modular software architecture, making it easy to extend with additional AI models such as Fire Detection, Intrusion Detection, PPE Compliance, and RTSP Camera Monitoring.

✨ Features

🎯 AI Detection

Real-Time Person Detection
Mobile Phone Detection
Helmet Detection
No Helmet Detection
Safety Vest Detection
Weapon Detection
Triple YOLOv8 Model Architecture

📊 Live Monitoring

Live Webcam Monitoring
Professional Status Panel
Live Person Counter
Live Mobile Counter
Live Helmet Counter
Live No Helmet Counter
Live Safety Vest Counter
Live Weapon Counter
Live FPS Counter
Live Date & Time

🚨 Violation Management

Mobile Violation Detection
No Helmet Violation Detection
Weapon Violation Detection
Frame-Based Event Confirmation
Duplicate Event Prevention
Modular Violation Manager

📸 Evidence Collection

Automatic Screenshot Capture
Timestamped Image Saving
Organized Screenshot Folder
Event-wise Screenshot Naming

📝 Event Logging

CSV Event Logging
Event Timestamp
Person Count
Mobile Count
Helmet Count
No Helmet Count
Vest Count
Weapon Count
Screenshot Name

📊 Dashboard

Tkinter Dashboard
Live Statistics
Latest Event Viewer
Latest Screenshot Viewer
Dashboard Auto Refresh
Event Analytics
CSV-based Monitoring

🏗️ Software Architecture

Modular Python Project
Object-Oriented Design
Multiple AI Model Support
Event Manager
Violation Manager
Screenshot Manager
Logger Module
Reusable Drawing Module
Clean Code Structure

📂 Project Structure

Smart_Safety_Monitor/

│
├── dashboard/
│   ├── __init__.py
│   ├── analytics.py
│   └── dashboard.py
│
├── docs/
│   └── images/
│
├── logs/
│
├── models/
│   ├── coco/
│   ├── ppe/
│   └── weapon/
│
├── output/
├── screenshots/
├── videos/
│
├── utils/
│   ├── camera.py
│   ├── constants.py
│   ├── date_time.py
│   ├── detector.py
│   ├── drawing.py
│   ├── event_manager.py
│   ├── fps.py
│   ├── logger.py
│   ├── mobile_detector.py
│   ├── ppe_detector.py
│   ├── screenshot.py
│   ├── violation_manager.py
│   └── weapon_detector.py
│
├── main.py
├── test_ppe_model.py
├── test_ppe_video.py
├── test_weapon_model.py
├── requirements.txt
├── README.md
└── .gitignore

🛠️ Tech Stack

Programming Language

Python 3.10

Computer Vision

OpenCV

Deep Learning

YOLOv8 (Ultralytics)

Framework

PyTorch

Dashboard

Tkinter

Data Processing

Pandas
NumPy

Visualization

OpenCV Drawing API

Logging

CSV

Version Control

Git
GitHub

🚀 Installation

1️⃣ Clone the Repository

git clone https://github.com/vikas-tikapur/Smart_Safety_Monitor.git

cd Smart_Safety_Monitor

2️⃣ Create a Virtual Environment

py -3.10 -m venv venv

3️⃣ Activate the Virtual Environment

Windows PowerShell

.\venv\Scripts\Activate.ps1

Windows Command Prompt

venv\Scripts\activate

4️⃣ Install Required Packages

pip install -r requirements.txt

▶️ Running the Application

Start Smart Safety Monitor

python main.py

Open Dashboard

python -m dashboard.dashboard

Test PPE Model

python test_ppe_model.py

Test PPE Video

python test_ppe_video.py

Test Weapon Detection Model

python test_weapon_model.py

🤖 AI Models

The project uses multiple YOLOv8 models for different detection tasks.

Model	Purpose	Status
YOLOv8 COCO	Person Detection	✅
YOLOv8 COCO	Mobile Phone Detection	✅
PPE YOLOv8	Helmet Detection	✅
PPE YOLOv8	No Helmet Detection	✅
PPE YOLOv8	Safety Vest Detection	✅
Weapon YOLOv8	Weapon Detection	✅

🧠 Detection Pipeline

Live Camera
      │
      ▼
 Frame Capture
      │
      ▼
──────────────────────────────────
YOLOv8 COCO Detector
──────────────────────────────────
      │
      ├── Person Detection
      └── Mobile Detection
      │
      ▼
──────────────────────────────────
PPE YOLOv8 Detector
──────────────────────────────────
      │
      ├── Helmet
      ├── No Helmet
      └── Safety Vest
      │
      ▼
──────────────────────────────────
Weapon YOLOv8 Detector
──────────────────────────────────
      │
      └── Weapon Detection
      │
      ▼
Violation Manager
      │
      ▼
Event Manager
      │
      ├── Screenshot Manager
      ├── CSV Logger
      └── Dashboard

📈 Current Progress

Module	Status
Project Architecture	✅
Modular Design	✅
Camera Module	✅
YOLOv8 COCO Detection	✅
Person Detection	✅
Mobile Detection	✅
PPE Detection	✅
Helmet Detection	✅
No Helmet Detection	✅
Safety Vest Detection	✅
Weapon Detection	✅
Drawing Module	✅
Screenshot Manager	✅
CSV Event Logging	✅
Event Manager	✅
Violation Manager	✅
Dashboard	✅
Dashboard Analytics	✅
Live Counters	✅
Auto Refresh	✅
Documentation	✅

📊 Project Completion

Component	Progress
Core Architecture	100%
AI Detection	100%
Dashboard	100%
Event Management	100%
Violation Management	100%
Documentation	100%
Code Cleanup	100%

🎯 Overall Completion

≈ 98%

The remaining work consists of optional enterprise-level features such as:

RTSP Camera Support
Email Alerts
Audio Alarm
Multi-Camera Monitoring
AI Reports

These features are planned for future releases and are not required for Version 1.0.

📦 Current Release

Version 1.0.0 Release Candidate (RC)

✔ Completed

Triple YOLOv8 Model Architecture
Person Detection
Mobile Detection
PPE Detection
Weapon Detection
Live Monitoring Dashboard
Screenshot Capture
CSV Logging
Event Manager
Violation Manager
Professional Monitoring Panel
Live Statistics
Code Cleanup
Documentation

🏗️ System Architecture

                           Live Camera
                                │
                                ▼
                        Video Frame Capture
                                │
        ┌───────────────────────┼────────────────────────┐
        ▼                       ▼                        ▼
 ┌────────────────┐     ┌────────────────┐      ┌────────────────┐
 │ YOLOv8 COCO    │     │ PPE YOLOv8     │      │ Weapon YOLOv8  │
 │                │     │                │      │                │
 │ • Person       │     │ • Helmet       │      │ • Weapon       │
 │ • Mobile       │     │ • No Helmet    │      │                │
 │                │     │ • Safety Vest  │      │                │
 └────────────────┘     └────────────────┘      └────────────────┘
        │                       │                        │
        └───────────────┬───────┴───────────────┬────────┘
                        ▼
              Detection Aggregation
                        │
                        ▼
               Violation Manager
                        │
                        ▼
                 Event Manager
                        │
        ┌───────────────┼────────────────┐
        ▼               ▼                ▼
 Screenshot      CSV Event Logger   Live Dashboard
   Manager                               │
                                         ▼
                              Dashboard Analytics

📸 Project Preview

🖥️ Live Monitoring

👷 Helmet Detection

🚫 No Helmet Detection

🔫 Weapon Detection

📊 Dashboard

🎯 Project Goals

The primary objective of this project is to build a modular AI-powered workplace safety monitoring system capable of detecting safety violations in real time.

Current goals achieved:

✅ Real-time workplace monitoring
✅ Multi-model AI detection
✅ Modular architecture
✅ Event-based violation management
✅ Automated screenshot capture
✅ CSV event logging
✅ Live monitoring dashboard
✅ Professional code structure
✅ Extensible architecture

🚀 Future Roadmap

Version 1.1

RTSP/IP Camera Support
Video File Processing
Email Alerts
Audio Alarm
Dashboard Charts
Daily Reports
Better Dashboard UI

Version 1.2

Multi-Camera Monitoring
Face Recognition
Attendance System Integration
Fire Detection
Smoke Detection
Restricted Area Detection

Version 2.0

Cloud Dashboard
Web Application
User Authentication
AI Safety Reports
Database Integration
REST API
Docker Deployment
Edge AI Deployment

💼 Resume Highlights

This project demonstrates practical experience in:

Python Development
Computer Vision
Deep Learning
YOLOv8
OpenCV
Object-Oriented Programming
Modular Software Architecture
Event-Driven Programming
Dashboard Development
Real-Time Video Processing
AI-Based Workplace Safety Monitoring

⭐ Why This Project?

This project is designed to simulate a real-world industrial safety monitoring solution.

It combines multiple AI models into a single modular application capable of monitoring workplace safety in real time while generating evidence, logs, and analytics.

The architecture is scalable and can easily be extended with additional AI models, making it suitable for future enterprise-level surveillance applications.

👨‍💻 Author

Vikas Mishra

AI / ML Developer | Python Developer | Computer Vision Enthusiast

Connect with Me

GitHub: https://github.com/vikas-tikapur
Portfolio: https://vikas-tikapur.github.io/portfolio-website/index.html

📄 License

This project is intended for educational purposes and portfolio demonstration.

You are free to fork, learn from, and improve this project while giving appropriate credit.

🤝 Contributing

Contributions are always welcome!

If you have ideas for improving this project:

Fork the repository
Create a new feature branch

git checkout -b feature-name

Commit your changes

git commit -m "Add new feature"

Push to your branch

git push origin feature-name

Open a Pull Request

🧪 Tested On

Windows 11
Python 3.10
OpenCV
Ultralytics YOLOv8
PyTorch
Tkinter

📌 Project Statistics

Programming Language

Python

AI Models

YOLOv8 COCO
YOLOv8 PPE
YOLOv8 Weapon

Detection Modules

Person Detection
Mobile Detection
Helmet Detection
No Helmet Detection
Safety Vest Detection
Weapon Detection

Event System

Screenshot Manager
CSV Logger
Event Manager
Violation Manager

Dashboard

Live Monitoring
Analytics
Latest Events
Latest Screenshot
Auto Refresh

🎓 Learning Outcomes

This project helped in learning:

Object-Oriented Programming
Modular Software Development
OpenCV
YOLOv8 Integration
Multiple AI Model Integration
Event-Driven Programming
CSV Logging
Dashboard Development
Real-Time Computer Vision
Software Architecture Design
Git & GitHub Workflow
Debugging and Testing

🔮 Future Enhancements

RTSP Camera Support
Multi-Camera Monitoring
Email Notifications
Telegram Alerts
Audio Alarm
Fire Detection
Smoke Detection
PPE Compliance Reports
Cloud Dashboard
REST API
Docker Deployment
Database Integration
User Authentication

🏆 Project Highlights

✔ Triple YOLOv8 Model Architecture

✔ Real-Time Workplace Monitoring

✔ AI-Based Safety Violation Detection

✔ Modular Python Architecture

✔ Automated Screenshot Capture

✔ Event Logging

✔ Dashboard Analytics

✔ Professional Monitoring Panel

✔ Live Statistics

✔ Production-Ready Project Structure

🙏 Acknowledgements

Special thanks to the open-source community and the developers behind:

Ultralytics YOLOv8
OpenCV
PyTorch
Pandas
NumPy

These libraries made it possible to build a real-time AI-powered workplace safety monitoring application.

⭐ Support

If you found this project useful:

⭐ Star this repository

🍴 Fork this repository

💡 Share your suggestions

🤝 Contribute to future improvements

🚀 Version