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YOLOv8-Based Surveillance Robot for Real-Time Threat Assessment and Mitigation

Yasmine Hany, Youssef Kelg, Nouran El Bendary, Youssef W. Abdelshafy, Gehad I. Alkady, Moheb Mekhail

Year
2024
Citations
1

Abstract

This research presents the development of a sophisticated autonomous surveillance robot designed to enhance security measures. Equipped with cutting-edge sensors, advanced image processing capabilities, and autonomous navigation, the robot effectively detects and responds to threats in real-time. The system utilizes the You Only Look Once (YOLO) v8 neural network for accurate threat identification, while robust hardware and software integration ensure reliable performance across diverse environments. By combining these elements, the research demonstrates the potential of spy robots in safeguarding communities and individuals from emerging security challenges. The spy robot is adept in real time threat evaluation, continuous monitoring with minimal human intervention. Some properties included accurate threat detection, localization, and classification. The main threat detection module uses YOLOv8 which attains an accuracy level of 92%. The system was verified to be reliable during tests conducted. Technological advances such as these require collaboration amongst different disciplines.

Keywords

Computer scienceRobotMobile robotArtificial intelligenceComputer security

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