Um die Herausforderungen in Bezug auf Klima und Regulierung für Schweizer Pensions- und Immobilienfonds zu bewältigen, zielt dieses Projekt darauf ab, transparente, technologie- und datengesteuerte Methoden zur Bewertung von Schweizer Immobilienanlagen in Bezug auf Gebäudezustand, CO2-Emissionen (aktuell und ...

The project aims to create a set of science-based methods to systematically translate acute and chronic physical risk scenarios into the (de-)valuation of buildings over time based on building characteristics (material, roof coverage, etc.), geographic location and risk level. This will allow companies to develop ...

We propose a fully digital, science-based solution that can provide forward-looking guidance for companies regarding the financial risks associated with biodiversity loss. We intend to communicate understandable risk metrics using User Interface to a biodiversity-committed network of stakeholders.  ...

We develop and adopt geoprocessing workflows to analyze and model the spatial footprints of companies representing company venues, production sites, or in general areas where companies are active. We combine the spatial environmental assessments with LCA methods to transform non-spatialized into spatialized ...

Innosuisse supports our research "Quantifying Illegal Activity: Estimating Dark Rates and Predicting Offenses in Switzerland." In collaboration with LogObject AG and the University of Zurich (UZH), we will estimate the number of undetected cyber-attacks and predict high-risk areas for burglaries using real life data ...