Construction-Hazard-Detection
About Enhances construction site safety using AI system
Listed in categories:
ConstructionSecurityGitHub
Description
Construction Hazard Detection is an AI-driven tool aimed at enhancing safety on construction sites. Utilizing the YOLOv8 model for object detection, this system identifies potential hazards such as workers without helmets, workers without safety vests, workers in close proximity to machinery, and workers near vehicles. Postprocessing algorithms are employed to enhance the accuracy of the detections. The system is designed for deployment in real-time environments, providing immediate analysis and alerts for detected hazards.
How to use Construction-Hazard-Detection?
Before running the application, configure the system by specifying the details of the video streams and other parameters in a YAML configuration file. Launch the hazard detection system in Docker or Python environment after configuration.
Core features of Construction-Hazard-Detection:
1️⃣
Real-time hazard detection using YOLOv8 model
2️⃣
Postprocessing algorithms for improved detection accuracy
3️⃣
Integration with LINE Messenger, WeChat, and Telegram for notifications
4️⃣
Ability to define controlled zones using safety cones
5️⃣
Configuration of multiple video streams for monitoring
Why could be used Construction-Hazard-Detection?
| # | Use case | Status | |
|---|---|---|---|
| # 1 | Monitoring construction sites for safety compliance | ✅ | |
| # 2 | Sending real-time alerts to site managers about detected hazards | ✅ | |
| # 3 | Defining and monitoring controlled zones to ensure worker safety | ✅ | |
Who developed Construction-Hazard-Detection?
The maker of this product is Yi Hung Wong, who has developed this tool to enhance safety in construction environments using advanced AI techniques and machine learning models.