Introduction: Natural and human-made disasters pose significant threats to public safety, healthcare infrastructure, and global economic stability. The increasing frequency and severity of these events have highlighted the need for innovative approaches to improve disaster preparedness, response, and resilience.
Objective: This narrative review aimed to investigate the role of artificial intelligence (AI) in enhancing disaster response and public safety.
Materials and Methods: This narrative review was conducted using reputable databases, including PubMed, Web of Science, Scopus, SID, and Magiran, as well as the search engines Google Scholar and Semantic Scholar. Articles published between 2018 and 2024 in the fields of artificial intelligence, disaster management, and public safety were reviewed. Persian- and English-language studies were included. The keywords “Artificial Intelligence,” “Disaster Management,” “Public Safety,” and “Disaster Response” were searched in both Persian and English. Ultimately, the findings of 10 relevant articles were analyzed.
Results: Artificial intelligence plays a substantial role in improving preparedness, response, and resilience among disaster response personnel in disaster management. Predictive analytics tools enable the forecasting of natural disasters and post-disaster disease outbreaks, thereby assisting responders in planning and preparedness efforts. Real-time monitoring systems collect and analyze diverse data sources and provide accurate situational information, enabling responders to make timely and effective decisions during emergencies. In addition, AI enhances resource optimization, improves patient triage, and facilitates telemedicine services, thereby strengthening the resilience of healthcare workers and disaster-affected populations. Collectively, these applications contribute to improved public safety and more effective disaster management.
Conclusion: The integration of artificial intelligence into disaster management can enhance the preparedness and resilience of both disaster responders and affected populations. However, challenges such as data privacy, algorithmic bias, and inadequate workforce training must be addressed to ensure optimal implementation. Training disaster response personnel to effectively utilize AI-based technologies is essential for maximizing their benefits.