Achieving sustainable housing in smart cities: the role of model-based engineering in developing complex systems in line with vision 2030
Rapid urbanization presents significant challenges for sustainable housing, often exposing the inadequacies of traditional planning methods. This study addresses this critical gap by proposing Model-Based Engineering (MBE) as a transformative solution. Employing a mixed-methods framework that integrates computational modeling (BIM, GIS), data analytics, and case studies such as NEOM, the research demonstrates that MBE can significantly enhance urban sustainability. Key findings indicate a 15% reduction in carbon emissions, a 20% decrease in energy consumption, and improved urban resilience under extreme conditions. These results surpass traditional approaches and highlight the integration of renewable energy sources and adaptive infrastructure. The study provides actionable strategies for policymakers and urban planners, presenting a replicable model that aligns with Saudi Arabia's Vision 2030 and supports sustainable urban development. Future research directions will focus on integrating AI for predictive modeling and exploring MBE’s applicability in diverse urban contexts worldwide. By harmonizing technology with sustainability, MBE emerges as a pivotal tool for creating resilient urban environments that ensure long-term environmental and economic benefits.
The study assesses the spatial distribution of early childhood schools in northern Riyadh using Geospatial systems to support Saudi Vision 2030 goals of equity and quality of life.
يهدف هذا البحث إلى تحليل أثر محطات قطار الرياض على أسعار الأراضي السكنية المجاورة من وجهة نظر العقاريين، من خلال دراسة تطبيقية على محطة د. سليمان الحبيب بحي الياسمين.
أصبحت "المدن العالمية" هدفاً استراتيجياً للعديد من صانعي السياسات الحضرية لا سيما مع التحولات الاقتصادية والتطور في القطاع المعلوماتي.