Weapon detection technologies for surveillance under different YoloV8 models on primary data: smart city based approach for safe society

This comparison between the yolov8s.pt and yolov8x.pt YOLOv8 models is very important for real-time applications, particularly for object recognition and surveillance. Based on the results, the 95% precision and recall of the yolov8s.pt model, together with its 96% mean average precision, demonstrate the model's usefulness in situations requiring precise and quick object recognition. This model has potential applications in a variety of security systems, supporting security protocols in high-risk areas such as airports, public areas, and high-security enterprises by assisting in the quick identification of possible threats in real-time surveillance data. Conversely, the yolov8x.pt model's better performance - which includes an astounding 98% precision and 99% mean average precision -highlights its effectiveness in demanding real-time applications that need exacting accuracy. Because of its complex capabilities, the model is a great fit for use in cutting-edge applications that require quick and accurate object recognition, such as autonomous driving technologies and sophisticated surveillance systems.