Author(s):
1. Ayaz Ali:
Deparment of Computer Systems Engineering, Mehran Univeristy of Engineering and Technology,Jamshoro,Pakistan
2. Atif Nawaz:
Deparment of Computer Systems Engineering, Mehran Univeristy of Engineering and Technology,Jamshoro,Pakistan
3. Aaqib Ali Sahito:
Department of Telecommunication Engineering, University of Sindh,Jamshoro,Pakistan
4. Asim Irfan:
Deparment of Computer Systems Engineering, Mehran Univeristy of Engineering and Technology,Jamshoro,Pakistan
Abstract:
In recent years, the development of intelligent autonomous surveillance applications has greatly benefited from the integration of object detection techniques. Among these techniques, human detection has emerged as a crucial component in surveillance systems, enabling the detection and monitoring of suspicious activities. With the rising crime rates, the demand for enhanced security measures has grown significantly. In this research paper, we propose a security system that utilizes YOLOv3, a state-of-the-art object detection model, for human detection. Our system is designed to instantly notify us when humans are detected, ensuring a swift response to potential security threats. By employing email and text message notifications, our system promptly alerts us of human presence. Through extensive evaluation, our proposed network demonstrates impressive performance in detecting humans, regardless of their proximity to the camera. Our application outperforms existing surveillance detection systems, further enhancing the effectiveness of security monitoring.
Page(s):
1-1
DOI:
DOI not available
Published:
Journal: Second International Conference on Computing Technologies, Tools and Applications (ICTAPP-24), June 4-6,2024 (Abstract Book), Volume: 0, Issue: 0, Year: 2024
Keywords:
Security
,
Image Processing
,
Object Detection
,
YOLOV3
,
Human Detection
,
Computer Vision
References:
References are not available for this document.
Citations
Citations are not available for this document.