AI-Driven Innovations in Earthquake Risk Mitigation: A Future-Focused Perspective

被引:1
|
作者
Plevris, Vagelis [1 ]
机构
[1] Qatar Univ, Dept Civil & Environm Engn, POB 2713, Doha, Qatar
关键词
artificial intelligence (AI); earthquake risk mitigation; seismic hazard mapping; structural health monitoring; multi-hazard risk assessment; earthquake-resilient design; real-time data integration;
D O I
10.3390/geosciences14090244
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
This study explores the transformative potential of artificial intelligence (AI) in revolutionizing earthquake risk mitigation across six key areas. Unlike traditional approaches, this paper examines how AI-driven innovations can uniquely enhance early warning systems, enabling real-time structural health monitoring, and providing dynamic, multi-hazard risk assessments that seamlessly integrate seismic data with other natural hazards such as tsunamis and landslides. It introduces groundbreaking applications of AI in earthquake-resilient design, where generative design algorithms and predictive analytics create structures that optimally balance safety, cost, and sustainability. The study also presents a novel discussion on the ethical implications of AI in this domain, stressing the critical need for transparency, accountability, and bias mitigation. Looking forward, the manuscript envisions the development of advanced AI platforms capable of delivering real-time, personalized risk assessments, immersive public training programs, and collaborative design tools that adapt to evolving seismic data. These innovations promise not only to significantly enhance current earthquake preparedness but also to pave the way toward a future where the societal impact of earthquakes is drastically reduced. This work underscores the potential of AI's role in shaping a safer, more resilient future, emphasizing the importance of continued innovation, ethical governance, and collaborative efforts.
引用
收藏
页数:28
相关论文
共 50 条
  • [41] Shaping the Future of IBD Diagnostics: A Multicentric AI-Driven Capsule Endoscopy Study
    Cardoso, P.
    Mascarenhas, M.
    Mendes, F.
    Afonso, J.
    Ribeiro, T.
    Martins, M.
    Mota, J.
    Almeida, M. J.
    Goncalves, T. Curdia
    Campelo, P.
    Macedo, C.
    Costa, A.
    Santander, C.
    di Palma, J.
    Ferreira, J.
    Cotter, J.
    Macedo, G.
    JOURNAL OF CROHNS & COLITIS, 2025, 19 : i245 - i245
  • [42] The future of patient education: A study on AI-driven responses to urinary incontinence inquiries
    Rotem, Reut
    Zamstein, Omri
    Rottenstreich, Misgav
    O'Sullivan, Orfhlaith E.
    O'reilly, Barry A.
    Weintraub, Adi Y.
    INTERNATIONAL JOURNAL OF GYNECOLOGY & OBSTETRICS, 2024, 167 (03) : 1004 - 1009
  • [43] AI-Driven EEC for Healthcare IoT: Security Challenges and Future Research Directions
    Adil, Muhammad
    Khan, Muhammad Khurram
    Farouk, Ahmed
    Jan, Mian Ahmad
    Anwar, Adnan
    Jin, Zhanpeng
    IEEE CONSUMER ELECTRONICS MAGAZINE, 2024, 13 (01) : 39 - 47
  • [44] AI-driven triage in emergency departments: A review of benefits, challenges, and future directions
    Da'Costa, Adebayo
    Teke, Jennifer
    Origbo, Joseph E.
    Osonuga, Ayokunle
    Egbon, Eghosasere
    Olawade, David B.
    INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS, 2025, 197
  • [45] Automation Bias and Assistive AI Risk of Harm From AI-Driven Clinical Decision Support
    Khera, Rohan
    Simon, Melissa A.
    Ross, Joseph S.
    JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION, 2023, 330 (23): : 2255 - 2257
  • [46] AI-Driven Prediction and Mapping of Soil Liquefaction Risks for Enhancing Earthquake Resilience in Smart Cities
    Katsuumi, Arisa
    Cong, Yuxin
    Inazumi, Shinya
    SMART CITIES, 2024, 7 (04): : 1836 - 1856
  • [47] AI-driven innovations in user experience and service psychology in Chinese university libraries amid digital transformation
    Liu, Liping
    INTERNATIONAL JOURNAL OF MENTAL HEALTH NURSING, 2024, 33 : 31 - 31
  • [48] AI-driven innovations in Alzheimer's disease: Integrating early diagnosis, personalized treatment, and prognostic modelling
    Kale, Mayur
    Wankhede, Nitu
    Pawar, Rupali
    Ballal, Suhas
    Kumawat, Rohit
    Goswami, Manish
    Khalid, Mohammad
    Taksande, Brijesh
    Upaganlawar, Aman
    Umekar, Milind
    Kopalli, ndana Rajendra
    Koppula, Sushruta
    AGEING RESEARCH REVIEWS, 2024, 101
  • [49] A design perspective on how to tackle gender biases when developing AI-driven systems
    Ana Santana González
    Lucia Rampino
    AI and Ethics, 2025, 5 (1): : 201 - 218
  • [50] Edge AI-Driven Air Quality Monitoring and Notification System: A Multilocation Campus Perspective
    Wijaya, Chandra
    Andriyadi, Anggi
    Chen, Shi-Yan
    Wang, I-Jan
    Yang, Chao-Tung
    INNOVATIVE MOBILE AND INTERNET SERVICES IN UBIQUITOUS COMPUTING, IMIS 2024, 2024, 214 : 256 - 261