An A.I. Based Cost Estimation System for Material Sourcing with Product Recommendations for Architectural Designs

This research showcases the creation of ArchEstimate, an AI-based online tool made to help architects with estimating project expenses and choosing materials. The system utilizes Artificial Neural Networks (ANN) to generate precise cost predictions using project details like gross floor area and material choices. Moreover, it includes fuzzy logic for preliminary assessment and material choice, improving the accuracy of cost prediction. Studies demonstrate the high accuracy of ANN for cost estimation, ranging from 87% to 98% in the literature review. ArchEstimate successfully reached a 90%-97% precision rate in cost estimation for this project. The system received outstanding ratings in functional suitability, compatibility, interaction capability, and maintainability when evaluated according to ISO 25010:2023 standards. The findings show that ArchEstimate greatly enhances cost estimation in architectural projects, providing architects with a reliable tool for generating precise estimates and material suggestions. Future advancements may broaden its capabilities to involve subcontractors and architects, thereby enhancing its range and utility in the construction sector.