Earticle

초록

영어

This study proposes a fire disaster prevention system that analyzes CCTV video streams to detect multi-crowd movements in real time and evaluate potential risk levels. The system identifies early warning signs by assessing crowd density, movement speed, and directional changes, enabling rapid detection of hazardous situations in densely populated environments. The proposed method extracts motion vectors and behavioral features from sequential video frames to compute a risk index that reflects scene instability. Experimental results using synthetic and real CCTV data demonstrate that the model effectively distinguishes normal, alert, and evacuation states. These findings indicate that the system can provide timely early warnings and support prompt decision-making during fire-related emergencies.

목차

Abstract
1. Introduction
2. Background & Related Work
3. Methodology
3.1 Data Collection and Preprocessing
3.2 Crowd Movement Analysis
3.3 Risk Evaluation Model
4. Experiments and Results
4.1 Experimental Setup and Datasets
4.2 Validation Using Real Crowded Images and Video Sequences
5. Conclusion
References

키워드

저자

• Dongjin Han [ Professor, Department of Fire and Disaster Prevention, Kyungil University, Korea ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  The International Journal of Advanced Smart Convergence

• 간기

  계간

• pISSN

  2288-2847

• eISSN

  2288-2855

• 수록기간

  2012~2025

• 십진분류

  KDC 326 DDC 380