Enhancing energy sustainability of building projects through nature-based solutions: A fuzzy-based decision support system

Abstract

Statement of the Problem. Lack of an artificial intelligence (AI)-driven approach to optimize the application of nature-based solutions (NbS) for enhancing energy sustainability in building projects. This gap can result in suboptimal decision-making processes. Purpose. This study aims at introducing a decision support system (DSS) framework that fuses NbS with the power of fuzzy – based AI. The proposal seeks to support decision-makers and empower them with the capabilities of AI. Method. Through a systematic literature review, the aim was to first capture models’ input variables for the development of a DSS framework using fuzzy logic. Conclusions. Our findings underscore the significance of an integrated approach in energy-efficient building projects. The integration of NbS with fuzzy-based AI showcases substantial promise in augmenting decision-making processes, promoting optimized designs that align with both environmental and technological objectives. Practical implications. The proposed DSS framework can lead to improved building project outcomes, reduced environmental footprints, and more resilient infrastructure regarding energy consumption. Future Research Directions: further research endeavors should delve deeper into the practical implementation of the DSS framework across diverse engineering projects. Exploring variations of fuzzy-AI could further enhance the decision support system. Additionally, investigating the potential barriers and challenges in adopting this approach will be crucial in ensuring its widespread adoption.