Project Overview:
Background and Problem Statement: Traditional methods for monitoring safety and efficiency on construction sites face challenges with worker behavior and safety gear compliance. MechFusion AI addressed these issues by developing the Smart Construction Worker Tracking System using advanced machine vision techniques.
Objectives: The project aimed to:
- Track construction workers and ensure real-time safety compliance.
- Create motion profiles to evaluate safety behaviors.
- Implement a machine vision system for real-time tracking and analysis.
- Implement a machine vision system for real-time tracking and analysis.
Methodology: The project utilized YOLO for object detection and classification, integrated with a Jetson Nano and Arducam camera. Key phases included dataset collection, model training, and hardware implementation, with rigorous evaluation to ensure real-world effectiveness.
Results: The system achieved high accuracy in detecting safety gear compliance and recognizing worker actions. It was tested effectively in various conditions, demonstrating robust performance in real-time monitoring.
MechFusion AI’s Smart Construction Worker Tracking System exemplifies its expertise in applying cutting-edge technology to enhance safety and efficiency in the construction industry.
