
New York City has big goals for greenhouse gas (GHG) emissions reductions over the next decade, with a big portion of them coming from buildings. Energy efficiency retrofits will account for a significant amount of those GHG reductions and technology can play a part in helping to identify where inefficiencies are in a building’s envelope (exterior walls and roof).
Opportunity: Developed out of NYU’s Tandon School of Engineering, Building Diagnostic Robotics (BDR) created robotics tools and AI analytics to aid in assessing building envelope efficiency. With the support of OTI and the Department Citywide Administrative Service’s (DCAS) Division of Energy Management, the BDR team’s received a $50,000 planning grant from the National Science Foundation (NSF) and was later awarded a $1M grant to scale the program and provide data on buildings across the city.


Methodology: BDR uses a combination of a UAV (drone) that can take video, thermal, and LiDAR imaging of a building exterior and a robot that scans roofs utilizing Ground Penetrating Radar (GPR). The data is processed through an Artificial Intelligence (AI) to detect envelope defects in buildings.
Location: Several DCAS managed buildings in NYC


Project Timeframe: November 2023 – March 2025
Stakeholders |
New York University (NYU) |
Building Diagnostics Robotics (BDR) |
Department of Citywide Administrative Services (DCAS) |
Office of Technology and Innovation (OTI) |
Project Category |
Greenhouse Gas Emissions |
Buildings |
Robotics |