A Multi-Modal Pipeline for Automated Building Energy Performance Estimation at Urban Scale

Stuttgart Physical AI Workshop and Meetup - September 22, 2026

Sep 22, 2026 · Time to be announced

We present an automated pipeline for estimating building-level heating demand from heterogeneous urban data sources, without requiring on-site audits. The system extracts the physical building parameters required by the DIN 18599 monthly heat balance standard from three complementary sources: street-level imagery processed through a facade analysis pipeline, cadastral records from the German real estate register, and three-dimensional building models. The aggregated features are passed to machine learning models that predict the physical inputs to a deterministic DIN 18599 calculation, producing EPBD-compliant heating demand estimates at urban scale. The target applications include municipal heat planning under Germany's Heat Planning Act (Wärmeplanungsgesetz), renovation potential screening in support of EPBD Minimum Energy Performance Standards, and ESG-driven portfolio risk assessment for financial institutions operating under EU Taxonomy reporting requirements. By removing the dependency on costly on-site audits, this project makes systematic building energy assessment viable at the resolution and pace that current climate and regulatory mandates demand.

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In person · Impact Hub Stuttgart, Stuttgart, Baden-Württemberg, Germany

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