FORSEES SIGNED

Project "FORSEES" data sheet

The following table provides information about the project.

 Partnership

Take a look of project's partnership.

Map

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 Project objective

Many of today’s world challenges cover the domain of safety and civil society. In a world like this the need for doctors and diagnosticians of the complex building and infrastructures organisms is imperative and high-priority. The number of variables have exponentially risen and the expert point of view is becoming more and more out of reach. The gap that just some decades ago would have required some years of work experience can be closed nowadays only with the help of new technologies. Artificial Intelligence (AI) is displaying all its power for diagnosing pathologies and diseases in Human Medicine. Imagine to apply the same framework for buildings in order to have the real-time health of the living architectures. Computer science and data analytics are capable of extracting patterns from these data and of producing a knowledge graph of the external reality. The project integrates digital pattern perception with human percepetion models. This models are object of studies for cognitive neurosciences, and by monitoring neurofunctional activity it could be possible to grasp and interpret where a structural intuition resides when a human performs related simple tasks. This structural intuition, in form of a mathematical structure (algorithmic relations), would create an AI tool as structural assistant to see the forces alive by a Computer Vision device. It would represent the growth of a sixth sense for real time structural analyses, building risk perception and architectures performance investigation. The chosen research institutions to carry out in the project are: Structural Engineering Department (DISEG) of Politecnico di Torino, MIT Senseable City Lab and BioRobotic Institute of Scuola Superiore Sant’Anna di Pisa as Secondment. The intelligent structural assistant that represents the research goal will rise up the knowledge to the level of extensive prediction, opening humans to a knowledge based on imaging and exploring more than focus and execution.