Overview
HelmNet is a computer vision solution for construction safety compliance. Using Convolutional Neural Networks (CNNs), the system automatically classifies whether workers on a construction site are wearing safety helmets.
Business Problem
Construction sites are hazardous environments where safety gear compliance is critical. Manual monitoring of helmet compliance is labor-intensive and inconsistent.
Approach
- Data: Labeled images of construction workers with and without helmets.
- Model: CNN architecture for image classification (helmet / no helmet).
- Training: Data augmentation to improve generalization across lighting conditions and angles.
- Deployment: Designed for integration with site camera systems for real-time monitoring.
Key Techniques
- Convolutional Neural Network (CNN) architecture
- Image classification and object detection
- Data augmentation for robustness
- Transfer learning from pre-trained vision models
Tech Stack
Computer Vision CNN