Pankoz Chandra Roy; Arifin Sultana; Md. Yeakub Ali
Abstract
This study examines the concept of data-driven smart ecological urbanism, which aims to promote sustainable and environmentally conscious urban growth through the use of data-driven technology. The authors offer a thorough review of the current literature on the topic, particularly highlighting the advantages ...
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This study examines the concept of data-driven smart ecological urbanism, which aims to promote sustainable and environmentally conscious urban growth through the use of data-driven technology. The authors offer a thorough review of the current literature on the topic, particularly highlighting the advantages and challenges of data-driven methodologies in urbanism. They argue that data-driven urbanism can offer invaluable insights into ecological concerns and pinpoint areas that require development. However, they also underscore concerns related to data privacy, over-reliance on technology, and potential unexpected outcomes. This study reveals the potential of data-driven smart ecological urbanism, emphasizing the necessity of a cautious and analytical approach to ensure its sustainable and socially equitable application. This paper suggests that adopting data-driven smart ecological urbanism can substantially improve a city's sustainability and livability by providing deeper insights into the ecological ramifications of urban expansion. The integration of data analytics and machine learning bolsters cities' capacity to deliver more accurate environmental forecasts, paving the way for targeted interventions that mitigate negative impacts and promote urban resilience, and sustainability. Nevertheless, the incorporation of data-driven technology in urban planning is not without challenges. For data-driven urbanism to truly embody social justice and sustainability, it is crucial to address issues related to data privacy and security, unforeseen consequences, and dependency on technology. Without a comprehensive analysis of these concerns, the application of data-driven smart ecological urbanism might inadvertently introduce adverse effects on marginalized communities and fall short of its potential in supporting sustainable urban growth.
