A.I evolution impact on multi-criteria spatial decision support system: affordable smart cities in developing countries

Digital transitions and innovation will be able to establish economic opportunities, enhance services, and enable citizen engagement in smart cities. It will be able to solve several issues we’re facing right now in urban areas to let us reach a digital sustainable innovative city. These digital transitions are not only meant to help current innovative cities but also help finding solutions for cities in developing countries that already have huge lack of basic needs in their communities. Developing cities have poor air conditions, inadequate water availability, waste-disposal difficulties, high energy consumption, and other several issues. This shows the multiplicity and complexity in problems that should be solved through the management of a digital software to handle all these data. To reach a digital sustainable city in a developing country will need huge process of assessing the current situation, how we can improve the SDGs in this city and implement the right indicators to reach the ideal solutions. Therefore, the aim of the thesis is to be able to assess the implementation of indicators for developing an affordable smart city and houses through the development of a new multi-criteria spatial decision support system (MC-SDSS) for developing countries, while being able to do it through an interactive assessment impact tools with a GIS-based software. The methodology for this research follows a quantitative method of research based on experimental method where it analyses smart city projects in developing countries through Planet Smart City company in Torino, Italy through MC-SDSS. Based on this thesis one of the conclusions we can reach is that digital transitions and implementation of A.I technology will be able to assess which indicators are better to be implemented in a developing country to design an affordable, smart, sustainable, and healthy community.