This paper is a proposition of methodological and technological approaches that try to constitute a framework that introduces modern artificial intelligence (AI) technologies for decision-making in the adaptive reuse of cultural heritage (CH) processes. The research aims to accelerate and improve the quality of adaptive CH re-use. The complexity of the problem derives from some causes of different nature: lack of attention to this problem from the public administration and private investors; decision-making processes complicated by the need to connect with experts, located in different countries. Most professionals, related to the CH management, cannot access detailed data about already existing successful initiatives. The specific objective and goal of the research is the creation of an AI framework and eco-system for supporting the development and implementation of innovative business and governance models to fill up the investment gap in the adaptive re-use practices. The paper shortly describes the first steps for creating a platform designed and developed to assist and advice public entities, networked experts, private entrepreneurs and citizens in actions aiming at the valorisation of the historic and CH asset and its integration in different groups of countries to boost growth, job opportunities and social benefits, under overall sustainability constraints. The technical solutions here adopted are based on convergent methodology and networked expertise (e-expertise) technology, open data models and active knowledge extraction and processing, machine learning, collective intelligence, recommendation systems and predictive analytics, CH adaptive re-use, innovation business, and models and case-based reasoning methods. Examples of case studies giving the inception for the project components are given.
Collaborative intelligence cyber-physical system for the valorization and re-use of cultural heritage / Bonci, Andrea; Clini, Paolo; Martin, Rafael; Pirani, Massimiliano; Quattrini, Ramona; Raikov, Alexander. - In: JOURNAL OF INFORMATION TECHNOLOGY IN CONSTRUCTION. - ISSN 1874-4753. - ELETTRONICO. - 23:1(2018), pp. 305-323.