CCTVIntelliGuard: an intelligent edge-based human motion detection and alerting system for CCTV surveillance
| dc.contributor.author | Nithiyaraj, V | |
| dc.contributor.author | Sooriyaarachchi, SJ | |
| dc.date.accessioned | 2026-04-09T05:37:56Z | |
| dc.date.issued | 2025 | |
| dc.description.abstract | Conventional CCTV (Closed-Circuit Television) surveillance systems capture continuous video streams without intelligence, resulting in storage overhead, delayed incident response, and inability to differentiate human activity from irrelevant motion. This paper presents CCTV IntelliGuard, a lightweight edge-based module that enhances traditional CCTV systems with real-time human motion detection and logging. The system employs a hybrid approach combining OpenCV based motion detection with YOLOv8 (You Only Look Once) object detection model [1] , deployed on a Raspberry Pi 5 edge device. Upon detecting human activity and the system records timestamped video clips. This retrofit solution transforms conventional CCTV into intelligent surveillance with minimal additional infrastructure. And this is optimized computation through two-stage detection. | |
| dc.identifier.conference | ERU Symposium - 2025 | |
| dc.identifier.doi | https://doi.org/10.31705/ERU.2025.26 | |
| dc.identifier.email | vithursanaa.22@cse.mrt.ac.lk | |
| dc.identifier.email | sulochanas@cse.mrt.ac.lk | |
| dc.identifier.faculty | Engineering | |
| dc.identifier.issn | 3051-4894 | |
| dc.identifier.pgnos | pp. 56-57 | |
| dc.identifier.place | Moratuwa | |
| dc.identifier.proceeding | Proceedings of the ERU Symposium 2025 | |
| dc.identifier.uri | https://dl.lib.uom.lk/handle/123/25110 | |
| dc.language.iso | en | |
| dc.publisher | Engineering Research Unit | |
| dc.title | CCTVIntelliGuard: an intelligent edge-based human motion detection and alerting system for CCTV surveillance | |
| dc.type | Conference-Extended-Abstract |
