Titolo della tesi: TOWARDS SMART CITY MODELS: EVALUATION OF METHODS AND PERFORMANCE INDEXES FOR THE SMART URBAN CONTEXTS DEVELOPMENT
Nowadays, towns and metropolises still occupy an essential role in facing the challenges of global urbanization, evolving its capacity to respond to the citizen’s needs. Among the global challenges, the climate issue is rapidly forcing authorities and governments to provide sustainable and efficient solutions. In this framework, the importance of shifting from traditional urban planning to more inclusive and innovative ones is an urgent request. As a consequence, the Smart City concept was developed as a reliable key to the contemporary cities’ requalification. In literature several methods have been proposed to plan a Smart city, but, only a few of them have been applied to the urban context. Most of them are indeed theoretical and qualitative approaches, providing scenarios that have not been applied to real universities campus/cities/districts.
To cover this gap, this thesis presents a useful and reliable answer, investigating the relevance of a Smart Methodology that can guide the transformation from a model to a smart one.
First, an existing qualitative smart approach is described and integrated into this work, focusing its application on a university’s campus. This method, laying its foundation on a global and inclusive characterization of a smart model, is composed of different steps, wherein an important integration was done in this thesis. Then, this method was completely transformed into a quantitative and ex-post one to overcome its subjectivity that characterizes a qualitative scheme. To test its efficiency and reliability, a comparison with another smart approach was performed. Finally, the flexibility of this new quantitative smart methodology is demonstrated throughout its application on two urban contexts: highland villages and the Italian suburb.
Results of the analysis show that these smart methods are reliable and provide coherent results, becoming a useful instrument for designers and planners for the identification of the most performing Smart strategies.