Data Science for Disaster Preparedness and Recovery
Abstrak
Data science is playing an increasingly vital role in disaster preparedness and recovery by providing real-time insights, predictive analytics, and AI-driven decision support systems. By leveraging big data, remote sensing, and machine learning algorithms, emergency response teams can enhance disaster forecasting, optimize resource allocation, and improve post-disaster recovery efforts. This paper explores the applications of data science in disaster management, covering areas such as AI-powered risk assessment, real-time disaster monitoring, and predictive analytics for early warning systems. Additionally, challenges such as data accuracy, integration with existing emergency frameworks, and ethical considerations in crisis response are discussed, along with emerging trends in AI-driven disaster resilience..
Penulis (1)
Dr. Emily Carter
Akses Cepat
- Tahun Terbit
- 2025
- Bahasa
- en
- Sumber Database
- CrossRef
- DOI
- 10.71465/ajdsa1272
- Akses
- Open Access ✓