Improving the Energy Efficiency of Buildings with Data

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.  

Robotic rover with ground penetrating radar (GPR)
Robotic rover with ground penetrating radar (GPR)
Example of 360◦ image with annotations
Example of 360◦ image with annotations

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

Areas in green show detected sub-surface moisture, areas in yellow show above-surface moisture
Areas in green show detected sub-surface moisture, areas in yellow show above-surface moisture
Summary of Visual Defects for Roof Section
Summary of Visual Defects for Roof Section

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