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Journal of Engineering Research

Journal of Engineering Research

DOI

https://doi.org/10.70259/engJER.2025.931983

Abstract

Well-designed outdoor spaces are increasingly recognised as critical components of environmental sustainability and community building within higher education institutions. Among the most influential elements in shaping these spaces is the strategic selection of vegetation, which must balance aesthetics, functionality, ecological value, and long-term maintenance. However, traditional plant selection methods remain time-consuming, labour-intensive, and often dependent on subjective judgement, posing significant challenges for landscape architects and campus planners. This paper explores the application of artificial intelligence (AI) as a transformative solution to enhance the plant selection process in educational outdoor environments. It introduces a comprehensive AI-driven framework that integrates key variables—including suitable vegetation types, site-specific environmental conditions, and the diverse needs of campus users—to support more efficient and context-responsive design decisions. By leveraging AI’s capacity to analyse complex datasets and detect nuanced patterns, this approach enables landscape architects to make more informed, evidence-based, and adaptable choices. The proposed method empowers designers to create outdoor spaces that are not only visually engaging but also sustainable, climate-responsive, and tailored to the well-being of campus communities. Additionally, the tool contributes to the broader shift toward data-informed design practices in landscape architecture, aligning with global goals of resilience, environmental responsibility, and resource efficiency. The paper advocates for a scalable, scientifically grounded methodology that enhances both the quality and impact of campus landscapes, offering a forward-thinking model for educational institutions aiming to integrate sustainability into their physical environments.

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