TY - CHAP
T1 - Virtual Safety Engineer
T2 - from hazard identification to risk control in the age of AI
AU - Yazdi, Mohammad
AU - Adumene, Sidum
AU - Tamunodukobipi, Daniel
AU - Mamudu, Abbas
AU - Goleiji, Elham
PY - 2025
Y1 - 2025
N2 - This chapter studies the transformative integration of Artificial Intelligence (AI) in Virtual Safety Engineering (VSE), a progression that markedly enhances hazard identification and risk control across various industries. By employing advanced technologies such as digital twins, machine learning, and real-time data analytics, VSE significantly surpasses traditional safety methodologies by providing more accurate, efficient, and dynamic risk management solutions. The chapter explores diverse applications, demonstrating how industries such as aerospace, manufacturing, nuclear energy, construction, and healthcare leverage AI-enhanced tools for safety management. This chapter highlights the capabilities of AI in optimizing safety protocols and discusses the integration of sophisticated simulation tools and software platforms that facilitate proactive safety measures. Through comprehensive examples, it illustrates the practical applications and effectiveness of AI-driven VSE in real-world scenarios, thereby underscoring its pivotal role in future safety management practices.
AB - This chapter studies the transformative integration of Artificial Intelligence (AI) in Virtual Safety Engineering (VSE), a progression that markedly enhances hazard identification and risk control across various industries. By employing advanced technologies such as digital twins, machine learning, and real-time data analytics, VSE significantly surpasses traditional safety methodologies by providing more accurate, efficient, and dynamic risk management solutions. The chapter explores diverse applications, demonstrating how industries such as aerospace, manufacturing, nuclear energy, construction, and healthcare leverage AI-enhanced tools for safety management. This chapter highlights the capabilities of AI in optimizing safety protocols and discusses the integration of sophisticated simulation tools and software platforms that facilitate proactive safety measures. Through comprehensive examples, it illustrates the practical applications and effectiveness of AI-driven VSE in real-world scenarios, thereby underscoring its pivotal role in future safety management practices.
KW - Artificial intelligence
KW - Virtual safety engineering
KW - Hazard identification
KW - Predictive safety
KW - Management risk control
UR - https://www.scopus.com/pages/publications/86000078062
U2 - 10.1007/978-3-031-82934-5_5
DO - 10.1007/978-3-031-82934-5_5
M3 - Chapter
AN - SCOPUS:86000078062
SN - 9783031829369
T3 - Studies in Systems, Decision and Control
SP - 91
EP - 110
BT - Safety-centric operations research: innovations and integrative approaches
A2 - Yazdi, Mohammad
PB - Springer, Springer Nature
CY - Cham, Switzerland
ER -