PPE DETECTION USING YOLOV3 AND DEEPSORT(HELMET)

PPE DETECTION USING YOLOV3 AND DEEPSORT(HELMET)

P.Harshitha , P.Saiteja Yadav, P.Saarika

Guide: H.Packiaraj

Assistant Professor

Department of Artificial Intelligence  and Machine Learning (AI&ML)

Malla Reddy University, Hyderabad ,India

ABSTRACT –

The aim of the project is to utilize existing  CCTV camera infrastructure to assist

supervisors to monitor workers effectively by providing them with real time alerts.

PPE Detection  using YOLO and DeepSORT. YOLO (You Only Look Once) is a popular object detection algorithm  that can detect and classify objects in an image or video stream in real time.

DeepSORT (Deep Learning-based SORT) is a tracking algorithm that can track multiple  objects over time in a video stream. By combining YOLO and DeepSORT, you can not only detect  PPE in real time but also track the workers wearing the PPE. Implementing DeepSORT to track the  workers wearing PPE

and Integrating the YOLO and DeepSORT models with your existing CCTV  camera infrastructure.

By analyzing this YOLO and DeepSORT has the potential to significantly improve workplace  safety by providing real-time alerts to supervisors when workers are not wearing PPE(helmet,  goggle) .The result of this project is detecting the persons with proper PPE and without PPE.