Object Detection Enabled Security Camera with Email and Sound Alert
Dr. T. Vijaya Kumar, Divi Sushma · INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT · 2025
ABSTRACT The demand for sophisticated security solutions has surged due to evolving security threats. This research introduces an advanced intelligent surveillance system that leverages deep learning and computer vision to automate threat detection and provide immediate alerts. Utilizing the YOLO (You Only Look Once) architecture for real-time object detection, combined with OpenCV for video processing and TensorFlow for model optimization, the system offers automated threat classification, dual-alert mechanisms (local sound alarms and email notifications), and customizable detection settings. A web-based interface developed using Flask facilitates user interaction, while MySQL manages detection logs, user preferences, and system analytics. The system demonstrates significant improvements in response time, detection accuracy, and operational efficiency over traditional CCTV systems, making it ideal for residential, commercial, and industrial security applications. Keywords: Intelligent surveillance, deep learning, computer vision, threat detection, YOLO, automated security, real-time monitoring, object detection.