This paper presents an intelligent video monitoring system with automatic fire detection. The system is based on YOLO deep learning algorithms and contour analysis, enabling real-time video stream processing. The multi-level alert system is implemented through a desktop (Tauri), mobile (Flutter), and web application (Nuxt). A modular Rust-based architecture ensures performance and scalability. The potential for integrating WebRTC and the personnel tracking system is discussed.
| Mualliflar | Сокиев, Т.Р. |
|---|---|
| Jurnal | Рақамли технологияларнинг назарий ва амалий масалалари |
| Nashr sanasi | 2025-11-09 |
| Jild | 8 |
| Son | 4 |
| Betlar | 87-92 |
| Til | Rus |
| DOI | 10.62132/ijdt.v8i4.306 |
DOI: 10.62132/ijdt.v8i4.306 · Maqolaning asl sahifasi
искусственный интеллект, мониторинг пожаров, YOLO, компьютерное зрение, обработка в реальном времени, artificial intelligence, fire monitoring, YOLO, computer vision, real-time processing
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