Innovative Solutions to Enhance Quality and Environmental Management with Artificial Intelligence in Sustainable Architecture.

Abstract:

The world is undergoing a significant shift towards sustainable development despite increasing environmental and economic challenges arising from urban expansion and excessive consumption of natural resources. These transformations reflect a global commitment to achieving a balance between economic growth, environmental protection, and quality of life improvement. It is crucial to implement efficient practices in quality and environmental management as a means to minimize negative environmental impacts and enhance building performance. The research revealed a gap between theoretical knowledge and practical implementation in the use of advanced technology techniques for quality and environmental management at construction sites. However, the ineffective utilization of modern technologies to improve execution quality and environmental performance in architecture remains a key gap that must be addressed. This research aims to explore the root causes of these challenges and investigate the promising opportunities offered by modern digital technologies, such as artificial intelligence (AI), augmented reality (AR), and virtual reality (VR). AI, in particular, offers a range of applications to support quality and environmental management, including predictive analytics for risk management, automated equipment, robotic assistance, real-time project performance monitoring, resource optimization, quality and environmental performance assessment on-site, design enhancement, predictive maintenance, and operational efficiency improvements.

This is classified as Applied Research aimed at providing practical solutions to a real problem (How to Employ Artificial Intelligence to Enhance Quality and Environmental Management of Sustainable Architecture). It is Descriptive Analytical research that relies on analyzing and interpreting current phenomena.

The research relies on a descriptive analytical method to monitor the current reality of quality and environmental management practices in sustainable architecture, and to analyze the role of artificial intelligence in improving them. Additionally, it employs a quasi-experimental method to study the proposed models for integrating artificial intelligence into sustainable design and construction processes.

Keywords:

Artificial Intelligence, Quality & Environmental Management, Sustainable Architecture, Green Architecture.