Anomalous Weapon Detection for Armed Robbery Using Yolo V8
Improved surveillance systems provide early warnings and improve public safety. Such systems are desperately needed in light of the rising number of armed robberies in private and public places. A YOLOv8-based system specifically intended for CCTV-based armed robbery detection was developed to meet...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-05-01
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| Series: | Engineering Proceedings |
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| Online Access: | https://www.mdpi.com/2673-4591/92/1/85 |
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| author | Adrian Lester E. Reyes Jennifer C. Dela Cruz |
| author_facet | Adrian Lester E. Reyes Jennifer C. Dela Cruz |
| author_sort | Adrian Lester E. Reyes |
| collection | DOAJ |
| description | Improved surveillance systems provide early warnings and improve public safety. Such systems are desperately needed in light of the rising number of armed robberies in private and public places. A YOLOv8-based system specifically intended for CCTV-based armed robbery detection was developed to meet this demand in this study. The system identified weapons such as handguns, assault weapons, shotguns, and others in real-time, utilizing a custom-trained model. The system demonstrated a strong performance with an overall anomaly detection accuracy of 87.50%. The confidence level was 1.2 m (58.79) and 2 m (59.74) in determining the optimal height and distance considering the positioning of the CCTV camera. The low confidence level was attributed to the mixture of images from a general database from the Internet along with self-captured images that resulted in the overfitting of the datasets. Although improvements are needed to increase the confidence level by using real guns in training the model and reducing false negatives, the potential of YOLOv8 to enhance public safety has been confirmed by providing early warnings of armed robberies. |
| format | Article |
| id | doaj-art-649d3a98e1cf49b1b0f1ec30831b5bf8 |
| institution | Kabale University |
| issn | 2673-4591 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Engineering Proceedings |
| spelling | doaj-art-649d3a98e1cf49b1b0f1ec30831b5bf82025-08-20T03:27:24ZengMDPI AGEngineering Proceedings2673-45912025-05-019218510.3390/engproc2025092085Anomalous Weapon Detection for Armed Robbery Using Yolo V8Adrian Lester E. Reyes0Jennifer C. Dela Cruz1School of Electrical, Electronics, and Computer Engineering Mapúa University, Manila 1002, PhilippinesSchool of Electrical, Electronics, and Computer Engineering Mapúa University, Manila 1002, PhilippinesImproved surveillance systems provide early warnings and improve public safety. Such systems are desperately needed in light of the rising number of armed robberies in private and public places. A YOLOv8-based system specifically intended for CCTV-based armed robbery detection was developed to meet this demand in this study. The system identified weapons such as handguns, assault weapons, shotguns, and others in real-time, utilizing a custom-trained model. The system demonstrated a strong performance with an overall anomaly detection accuracy of 87.50%. The confidence level was 1.2 m (58.79) and 2 m (59.74) in determining the optimal height and distance considering the positioning of the CCTV camera. The low confidence level was attributed to the mixture of images from a general database from the Internet along with self-captured images that resulted in the overfitting of the datasets. Although improvements are needed to increase the confidence level by using real guns in training the model and reducing false negatives, the potential of YOLOv8 to enhance public safety has been confirmed by providing early warnings of armed robberies.https://www.mdpi.com/2673-4591/92/1/85YOLOrobberydetectionanomalous weapons |
| spellingShingle | Adrian Lester E. Reyes Jennifer C. Dela Cruz Anomalous Weapon Detection for Armed Robbery Using Yolo V8 Engineering Proceedings YOLO robbery detection anomalous weapons |
| title | Anomalous Weapon Detection for Armed Robbery Using Yolo V8 |
| title_full | Anomalous Weapon Detection for Armed Robbery Using Yolo V8 |
| title_fullStr | Anomalous Weapon Detection for Armed Robbery Using Yolo V8 |
| title_full_unstemmed | Anomalous Weapon Detection for Armed Robbery Using Yolo V8 |
| title_short | Anomalous Weapon Detection for Armed Robbery Using Yolo V8 |
| title_sort | anomalous weapon detection for armed robbery using yolo v8 |
| topic | YOLO robbery detection anomalous weapons |
| url | https://www.mdpi.com/2673-4591/92/1/85 |
| work_keys_str_mv | AT adrianlesterereyes anomalousweapondetectionforarmedrobberyusingyolov8 AT jennifercdelacruz anomalousweapondetectionforarmedrobberyusingyolov8 |