# Effective Strategies for Enhancing Real-Time Weapons Detection in Industry
## 5 Discussion  
Some key points can be drawn from the results. Firstly, the choice of the model version depends on the system being used; for example, it is recommended to utilise either the YOLOv8 small model for less powerful systems or the medium model for more \begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline
**BG** & **Augs** & **S.M.** & **Temp.** & **2 nd** & **Clas.** & **F1** & **mAP50** & **mAP75** & **mAP** & **FP** & \(FP_{\leq 100}\) \\ \hline - & - & - & - & - & 77.12 & 68.10 & 59.15 & 72.50 & 348 & 347 \\ - & - & - & x & - & 53.29 & 52.05 & 46.48 & 17.47 & 0 & 0 \\ - & - & - & - & x & 75.29 & 64.95 & 56.06 & 71.06 & 90 & 90 \\ - & - & - & x & x & 62.67 & 55.90 & 48.80 & 45.81 & 0 & 0 \\ - & x & - & - & - & 76.97 & 72.52 & 62.48 & 73.65 & 205 & 205 \\ - & x & - & x & - & 53.11 & 52.94 & 46.84 & 11.71 & 0 & 0 \\ - & x & - & - & x & 74.60 & 69.46 & 59.63 & 72.20 & 51 & 51 \\ - & x & - & x & x & 58.74 & 55.06 & 47.73 & 38.55 & 0 & 0 \\ - & - & x & - & - & 77.95 & 72.76 & 64.58 & 74.05 & 317 & 315 \\ - & - & x & x & - & 55.65 & 54.01 & 49.46 & 24.54 & 0 & 0 \\ - & - & x & - & x & 75.99 & 70.62 & 62.16 & 73.27 & 96 & 96 \\ - & - & x & x & x & 62.92 & 59.51 & 52.99 & 46.33 & 1 & 1 \\ - & x & x & - & - & 77.08 & 71.91 & 63.54 & 73.42 & 334 & 333 \\ - & x & x & x & - & 58.78 & 56.86 & 51.37 & 34.90 & 0 & 0 \\ - & x & x & - & x & 75.72 & 69.71 & 61.40 & 73.17 & 108 & 108 \\ \hline - & x & x & x & x & 68.89 & 65.56 & 57.83 & 58.05 & 0 & 0 \\ \hline x & - & - & - & - & 77.21 & 73.18 & 62.81 & 72.50 & 293 & 289 \\ x & - & - & x & - & 54.61 & 53.87 & 47.50 & 19.28 & 0 & 0 \\ x & - & - & - & x & 75.69 & 71.07 & 60.49 & 71.61 & 90 & 90 \\ x & - & - & x & x & 65.14 & 61.99 & 53.02 & 50.02 & 0 & 0 \\ x & - & - & - & - & 77.23 & 73.06 & 62.77 & 73.10 & 202 & 199 \\ x & - & x & - & - & 54.62 & 53.35 & 47.81 & 19.10 & 0 & 0 \\ x & - & - & - & x & 76.42 & 71.87 & 61.33 & 72.56 & 87 & 87 \\ x & - & x & x & x & 58.52 & 56.90 & 49.53 & 34.07 & 0 & 0 \\ x & - & x & - & - & 77.64 & 72.91 & 64.83 & 73.99 & 445 & 444 \\ x & - & x & x & - & 56.42 & 54.85 & 50.19 & 28.85 & 0 & 0 \\ x & - & x & - & x & 75.85 & 70.46 & 62.39 & 72.89 & 64 & 64 \\ x & - & x & x & x & 65.93 & 62.31 & 55.89 & 54.81 & 0 & 0 \\ x & - & x & - & - & 77.68 & 73.88 & 63.41 & 73.60 & 164 & 164 \\ x & - & x & x & - & 52.66 & 52.49 & 48.10 & 11.82 & 0 & 0 \\ \hline \hline \(\chi\) & \(\chi\) & \(\chi\) & - & x & 75.72 & 71.31 & 61.09 & 71.71 & 48 & 48 \\ \hline \hline \(\chi\) & \(\chi\) & \(\chi\) & \(\chi\) & \(\chi\) & \(\chi\) & 61.14 & 59.28 & 51.36 & 40.12 & 0 & 0 \\ \hline \hline \end{tabular}
\end{table} 
Table 11: General comparison between each possible combination. The symbol ‘\(\times\)’ indicates whether the combination is used. Note that BG images means Background Images, Augs means augmentations, S.M. means Scale Match, temp. wind. means temporal window, and 2 nd clas. mean second classifier. The metrics used were Average Precision (AP), AP50, AP75, F1 score (F1), False Positives (FP), false positives with an area less or equal to 100 \(px^{2}\) (\(FP_{\leq 100}\)) and mean frames per second (mFPS). These were calculated using an IoU of 0.7 and a confidence threshold of 0.5. Note that the results in red are the best and those in blue are the second best. powerful systems, whereas the large model may not be suitable for real-time tasks, and the improvement compared to the medium version is marginal. Regardless of the choice of version, it is crucial to apply augmentations that replicate the conditions of a CCTV system, keeping in mind that certain augmentations may negatively impact results due to lower image quality within the dataset. Additionally, using the Scale Match method is very useful for improving the detection of weapons with a low scale ratio. Due to the use of the YOLOv8's library to carry out the inference, the current detection system processes video feeds from multiple cameras sequentially.