AI-Powered Building Enclosure Diagnostics for Civic Infrastructure

The City of Savannah is partnering with Lamarr.AI to modernize how it evaluates and maintains five critical civic buildings — Fire Stations #3, 10, and 13, City Hall, and the Woodville Community Center — through advanced AI-enabled enclosure diagnostics and energy modeling. Each structure represents essential public infrastructure, yet their aging façades and roofs present rising lifecycle, safety, and energy-efficiency challenges. By deploying Lamarr.AI’s hybrid visual–thermal imaging and machine-learning platform, the project will create detailed assessments of building envelope health, identifying deficiencies such as thermal bridges, moisture intrusion, air leakage pathways, and other anomalies that typically go undetected through conventional inspections.

The initiative integrates drone-based data collection, infrared and RGB imaging, and computer vision algorithms to produce geolocated 2D and 3D maps of anomalies across each façade. These outputs will be paired with photogrammetry-generated as-built digital models, providing Savannah with actionable insights into deterioration patterns and targeted recommendations for repair. For one building, the project will also deliver a full energy performance model, quantifying the impact of envelope improvements on utility use, emissions reduction, and long-term cost savings.

Beyond the technical work, the pilot reflects Savannah’s broader commitment to sustainable capital planning and proactive asset management. Supported by the Partnership for Innovation, the project will culminate in leadership briefings and a clear roadmap for integrating AI diagnostics into the city’s long-term facilities strategy. By uniting cutting-edge analysis with practical implementation pathways, Savannah is positioning its civic buildings for greater resilience, fiscal stewardship, and operational efficiency.