2025: AR3-Lumber: AI-powered Reprocessing, Regrading, and Recertification of Salvage Lumber
Reclaiming lumber for reuse in construction dramatically reduces energy consumption and greenhouse gas emissions, as compared to new construction; however, lumber reclamation is often more expensive because of the need to individually assess for defects and reuse potential. This project – AR3-Lumber – convenes experts from industry and academia to develop and validate a scalable, AI-driven system for visual grading and reuse of reclaimed lumber in high-performance structural applications. AR3-Lumber promotes a more efficient and scalable approach to reclaimed wood processing and bridges the gap between circular economy principles and practical industry applications.
Investigators: Felix Heisel (Architecture, Art and Planning/Architecture), Steve Marschner (Bowers CIS/Computer Science), Matthew Reiter (Cornell Engineering/Civil and Environmental Engineering)