Earticle

초록

영어

The modern industrial environment is undergoing rapid changes driven by advancements in technology, creating new challenges for safety engineering, particularly in the construction industry. Traditional safety engineering models, which focus on physical accident prevention and post-incident responses, are proving insufficient to address the increasing complexity and dynamic risks introduced by the 4th Industrial Revolution. This study aims to propose a next-generation safety engineering model specifically tailored to the construction industry. The model integrates advanced technologies, such as Artificial Intelligence (AI), the Internet of Things (IoT), big data, and predictive analytics, to enable real-time risk detection, proactive management, and automated responses. By addressing the limitations of static risk management and human-centered approaches, the proposed model improves the ability to analyze and mitigate both physical and systemic risks. This research contributes to the field of safety engineering by introducing an innovative framework that combines modern digital tools with a systematic approach to risk management, ensuring enhanced safety and operational efficiency on construction sites. The study's outcomes demonstrate the model's effectiveness in identifying risks, predicting potential hazards, and implementing preventive measures to reduce accidents and enhance workplace safety.

목차

Abstract
1. INTRODUCTION
2. THEORETICAL BACKGROUND AND PREVIOUS RESEARCH
2.1 Developments and challenges in safety engineering
2.2 The Need for Next-Generation Safety Engineering
2.3 Limitations of Existing Technologies
2.4 Differentiated Features of the Proposed Technology
2.5 Comparison Between Existing and Proposed Models
2.6 Research Results Comparison
3. THREAT SPECIFICATION
3.1 Threat to security goal map
3.2 Attack method per asset map
3.3 Attack list
4. RISK EVALUATION
4.1 Offensive tree structuret
4.2 Attacker profile and attack likelihood
4.3 Risk Level of the Attack Target
4.4 Observation and Control of Attack Objectives
4.5 Risk Evaluation
4.6 Risk Assessment and Privacy Concerns in Automated Building Monitoring Systems
4.7 Safety and Security Challenges in Smart Building Communication Systems
5. EXPERIMENTAL SETUP AND RESULTS
5.1 Experimental Setup
5.2 Experimental Results
5.3 Discussiion
6. COUNTERMEASURES
7. CONCLUSION
REFERENCES

키워드

저자

• Sang-soo Kim [ Doctor Candidate, Department of IT Convergence, Hoseo University ]
• Seung-Jung Shin [ Associate professor, Department of ICT Convergence, Hoseo University ] 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