Automated Reverse Engineering System
A.R.E.S. is an AI powered 360 degree scanning system designed to capture physical spaces and hand drawn plans and convert them into accurate digital models. The concept originated with the Rochester subway system, which lacks current blueprints and proper documentation. This system will be able to document any environment or object that requires accurate records. All data captured and processed by the system is original, with no generation from copyrighted material, ensuring that all content is fully ethical and independently produced. Visitors will see the camera in action, observing how it collects comprehensive imagery of spaces or plans and how the AI processes that data into precise digital models. The system can translate both physical structures and hand drawn sketches into digital assets suitable for analysis, restoration, and creative reuse. Examples demonstrate how previously undocumented or deteriorating environments can be efficiently captured and converted into digital documents. The hardware is designed for adaptability and precision, capable of scanning irregular, confined, or complex environments. The AI organizes images, identifies key features, and converts them into CAD or blueprint elements with high accuracy. The exhibit will show how the hardware and software will work together to address real world challenges in documentation and preservation while maintaining ethical standards. This project will address current needs in restoration, planning, and preservation by reducing time and errors, and providing reliable records where none exist. Viewers will insight into the intersection of engineering, design, and AI technology, and learn how digital modeling can make unrecorded spaces accessible. The exhibit emphasizes practical applications, demonstrating how advanced imaging systems can bridge the gap between physical environments and digital tools while preserving both structural and cultural knowledge in an ethical and original manner. In addition, the exhibit will explore the legal and ethical implications of AI powered scanning and digital modeling, encouraging discussion about responsible use, ownership of captured data, and the larger impact of emerging technologies on preservation, restoration and design practices.
Topics
Exhibitor
Hannah Defilippo
Advisor(s)
Jess Liberman
Organization
Project is done in collaboration with the humanities computing and design program, and the subway restoration project
Thank you to all of our sponsors!






