Cong, Y.; Inazumi, S. Integration of Smart City Technologies with Advanced Predictive Analytics for Geotechnical Investigations. Smart Cities2024, 7, 1089-1108.
Cong, Y.; Inazumi, S. Integration of Smart City Technologies with Advanced Predictive Analytics for Geotechnical Investigations. Smart Cities 2024, 7, 1089-1108.
Cong, Y.; Inazumi, S. Integration of Smart City Technologies with Advanced Predictive Analytics for Geotechnical Investigations. Smart Cities2024, 7, 1089-1108.
Cong, Y.; Inazumi, S. Integration of Smart City Technologies with Advanced Predictive Analytics for Geotechnical Investigations. Smart Cities 2024, 7, 1089-1108.
Abstract
This paper addresses challenges and solutions in urban development and infrastructure resilience, particularly in the context of Japan's rapidly urbanizing landscape. It explores the integration of smart city concepts to combat land subsidence and liquefaction, phenomena highlighted by the 2011 Great East Japan Earthquake. Using advanced technologies such as smart sensing and predictive analytics through kriging and ensemble learning, the study aims to improve the accuracy of geotechnical investigations and urban planning. By analyzing data from 433 geotechnical surveys in Setagaya, Tokyo, it develops predictive models to accurately determine the depth of bearing layers critical to urban infrastructure. The results demonstrate the superiority of ensemble learning in predicting the depth of bearing layers, with significant implications for smart city development and the sustainability of urban environments. This interdisciplinary approach not only seeks to mitigate risks associated with geological disturbances, but also promotes sustainable urban growth that prioritizes safety and prosperity. Through advanced technology and comprehensive research, the study underscores the potential of smart cities to address urban complexities and ensure a resilient, sustainable future.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.