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Human Adaption to Climate Change: Marine Disaster Risk Reduction in the Era of Intelligence

Author

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  • Junyao Luo

    (College of Basic Education, National University of Defense Technology, Changsha 410073, China)

  • Aihua Yang

    (College of Basic Education, National University of Defense Technology, Changsha 410073, China)

Abstract

With the intensification of global warming and sea level rise, extreme weather and climate events occur frequently, increasing the probability and destructive power of marine disasters. The purpose of this paper is to propose the specific application of artificial intelligence (AI) in marine disaster risk reduction. First, this paper uses computer vision to assess the vulnerability of the target and then uses CNN-LSTM to forecast tropical cyclones. Second, this paper proposes a social media communication mechanism based on deep learning and a psychological crisis intervention mechanism based on AIGC. In addition, the rescue response system based on an intelligent unmanned platform is also the focus of this research. Third, this paper also attempts to discuss disaster loss assessment and reconstruction based on machine learning and smart city concepts. After proposing specific application measures, this paper proposes three policy recommendations. The first one is improving legislation to break the technological trap of AI. The second one is promoting scientific and technological innovation to break through key technologies of AI. The third one is strengthening coordination and cooperation to build a disaster reduction system that integrates man and machine. The purpose of this paper is to reduce the risk of marine disasters by applying AI. Furthermore, we hope to provide scientific references for sustainability and human adaptation to climate change.

Suggested Citation

  • Junyao Luo & Aihua Yang, 2024. "Human Adaption to Climate Change: Marine Disaster Risk Reduction in the Era of Intelligence," Sustainability, MDPI, vol. 16(22), pages 1-23, November.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:22:p:9647-:d:1514684
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    References listed on IDEAS

    as
    1. Adland, Roar & Jia, Haiying & Lode, Tønnes & Skontorp, Jørgen, 2021. "The value of meteorological data in marine risk assessment," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    2. Jung Woo Kim & Sang Hun Sul & Jae Boong Choi, 2018. "Development of unmanned remote smart rescue platform applying Internet of Things technology," International Journal of Distributed Sensor Networks, , vol. 14(6), pages 15501477187, June.
    3. Gelian Song & Meijuan Xia & Dahai Zhang, 2023. "Deep Reinforcement Learning for Risk and Disaster Management in Energy-Efficient Marine Ranching," Energies, MDPI, vol. 16(16), pages 1-20, August.
    4. Junyao Luo & Aihua Yang, 2024. "Analysis of Change in Summer Extreme Precipitation in Southwest China and Human Adaptation," Sustainability, MDPI, vol. 16(17), pages 1-21, August.
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