Scholarlink

<p>Urban open spaces (UOS) such as parks and recreational areas play a vital role in enhancing quality of life by supporting physical activity, social interaction, and stress relief. In dense, arid cities like Makkah, a gap persists between the provision of UOS and user needs. This study examines how UOS affect residents’ quality of life and explores the use of artificial intelligence (AI) to analyze user preferences through public reviews. A mixed-methods approach was adopted, combining survey data from 397 residents with AI-assisted analysis of Google Maps reviews using ChatGPT 4.0. Survey data were analyzed using SPSS 21 for descriptive statistics and reliability testing. Results show that age, visit frequency, and physical activity significantly influence users’ satisfaction, though overall satisfaction levels were modest. Common concerns such as safety, cleanliness, and accessibility were frequently mentioned in reviews, revealing a misalignment between planning and user expectations. The study proposed an integrated AI-supported framework for evaluating UOS, offering practical insights for policy makers, planners and designers which support Saudi Vision 2030’s goals of creating sustainable, human-centered urban environments, and improve residents’ quality of life.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Smart evaluation of Urban open spaces for quality of life enhancement: an AI-Driven conceptual framework based on evidence from Makkah, Saudi Arabia

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年7月28日

查看全文
  • Abdullah Karban

摘要

Urban open spaces (UOS) such as parks and recreational areas play a vital role in enhancing quality of life by supporting physical activity, social interaction, and stress relief. In dense, arid cities like Makkah, a gap persists between the provision of UOS and user needs. This study examines how UOS affect residents’ quality of life and explores the use of artificial intelligence (AI) to analyze user preferences through public reviews. A mixed-methods approach was adopted, combining survey data from 397 residents with AI-assisted analysis of Google Maps reviews using ChatGPT 4.0. Survey data were analyzed using SPSS 21 for descriptive statistics and reliability testing. Results show that age, visit frequency, and physical activity significantly influence users’ satisfaction, though overall satisfaction levels were modest. Common concerns such as safety, cleanliness, and accessibility were frequently mentioned in reviews, revealing a misalignment between planning and user expectations. The study proposed an integrated AI-supported framework for evaluating UOS, offering practical insights for policy makers, planners and designers which support Saudi Vision 2030’s goals of creating sustainable, human-centered urban environments, and improve residents’ quality of life.