Cognitive Adaptve Urban Systems for the Living Built Environment

Abstract

The research proposes the use of structured data systems to define by connected attributes the buildings, the users and the infrastructure information as the kay scenario of the future development of the Cognitive Adaptive Urban Systems able to learn and respond to sustainable requirement, users’ behavior and anticipating and supporting their needs. In order to test the usability and to demonstrate the potential of a georeferenced, integrated information system on buildings in a practical use case, Politecnico di Milano and University of Brescia are focusing on the implementation of a district-wide heating energy need estimation: assuming current TDB contents as rough informational basis for energy modeling. The study aims to progressively evaluate the benefits related to different levels of data enrichment. Starting from rough TDB data, building information are integrated initially with semantic data coming from other existing datasets and furtherly with geometric data coming from BIMs. The final goal of the research is to measure improvements in accuracy related to a progressive data refinement and, at the same time, evaluate costs and efforts required for the realization of such refinement. The proposed methodology is intended to support designers and decisionmakers, providing a fully-integrated design process moving into a digital environment in which to test and track the users to predict the effects of the built environment on the human wellbeing