A Study on the Development of IoT-based Green Infrastructure Management Solution Model

A Study on the Development of IoT-based Green Infrastructure Management Solution Model
発表者/presenter’s name:〇Yong-Hoon Ha 1,Gun-woo Kim 1
所属/Affiliation:1 Landscape Urbanism Major, Graduate School of Urban studies, Hanyang University

要旨/Abstract

This study introduces “LaaS (Landscaping as a Service),” an innovative IoT-based model aimed at enhancing the management of green infrastructure in response to the escalating climate crisis. Green infrastructure is increasingly recognized as pivotal in mitigating the consequences of climate change, yet deficiencies exist in efficient monitoring, control, and response systems, even in regions known for substantial urban landscaping investments.

The objectives of this research encompass a comprehensive assessment of current green infrastructure management, the development of an IoT-centric monitoring system, robust data analysis and interpretation using tools like Scikit-learn, operationalization of the LaaS concept, provision of an intuitive user interface, and formulation of strategic recommendations for future green infrastructure development.

Methods employed include Focus Group Interviews (FGI) involving experts from diverse fields, the deployment of IoT sensors to gather comprehensive data, data preprocessing and analysis with Scikit-learn, LaaS framework development, user interface design, and the synthesis of findings into well-informed recommendations.

Results highlight the critical role of IoT sensor data in managing and maintaining green infrastructure, emphasizing real-time data collection and analysis for tree health, soil conditions, and atmospheric parameters. The significance of Scikit-learn in effective data utilization and the creation of a user-friendly interface empowering real-time monitoring and management are also key outcomes.

In conclusion, this innovative IoT-based LaaS solution addresses post-construction challenges in managing green infrastructure in residential areas. Its outcomes are expected to significantly enhance urban environments’ ecological and social value, offering practical solutions for policymakers and urban planners, and stimulating further research and innovation in green infrastructure development and management.

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