Civil construction sites have a high-risk environment that exposes workers to mishaps such as falls or accidents arising from equipment failures or not wearing proper safety gear during work. Worker safety is an essential aspect of civil construction sites. Therefore, construction managers must regularly monitor the safety protocols. Using conventional methods for monitoring safety at work can be ineffective and time-consuming. A leading construction company had approached ThinkPalm to support them with an AI-based objection detection system to verify objects in real time to avoid accidents on their construction site. 

The Solution- ThinkPalm’s AI Object Detection Model 

ThinkPalm used its advanced AI for object detection with the help of computer vision and machine learning to avoid security incidents in civil construction sites. The designed detection system is based on the YOLOv8 model, an advanced object detection algorithm that identifies and localizes objects in real-time. Also, ThinkPalm installed multiple surveillance cameras to provide a feasible solution. The model trained on custom datasets detected personal protective equipment (PPE) items such as hard hats, gloves, boots, safety vests, goggles, and many more.