Abstract
This paper presents an AI-based Safety Monitoring System designed to enhance security and surveillance in various environments. The system integrates machine learning and computer vision techniques to detect potential threats, identify unauthorized access, and monitor real-time activities. The proposed system utilizes deep learning models for object detection, facial recognition, and anomaly detection, ensuring a high level of accuracy in identifying safety hazards. Experimental results demonstrate the system's effectiveness in improving response times and reducing false alarms, making it a viable solution for smart surveillance applications.
Keywords
Deep Learning Features; Medical Image Analysis; Alex Net; CNN Features.
Citations
IRE Journals:
Abhishek G P , Chethan R , Manoj N , Vijendra S N
"AI-Powered Surveillance Using Deep Learning" Iconic Research And Engineering Journals Volume 8 Issue 10 2025 Page 408-412
IEEE:
Abhishek G P , Chethan R , Manoj N , Vijendra S N
"AI-Powered Surveillance Using Deep Learning" Iconic Research And Engineering Journals, 8(10)
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