The Artificial Intelligence for Public Services (AI4Gov) Master’s Program aims to prepare future digital transformation leaders for AI in the public sector. The core objectives of the AI4Gov Program are providing education on (i) the management of AI-based public services, (ii) the usage of AI in public administration’s operations, and (iii) the governance of AI in the public sector and for the delivery of public services to society.
Oxana Casu, Paolo De Biase, and Jose Diaz Mendoza, supervised by Ilaria Mariani, Francesco Mureddu, Mauro Manente, and Gaetano Volpe, submitted a Thesis on SPOTTED: ‘releafMi’ – Releaf the city of Milan.
The purpose of the research is to prototype and pilot a user-oriented and dynamic tool to support a data-driven decision-making approach in public administration to mitigate the heat island effect and other environmental challenges in the city of Milan. The tool also aims to facilitate communication between the administration and the community, promoting the development of positive synergies between the public and private sectors. This is consistent with the Milan municipality’s goals of ‘going green’ and promoting the development of environmental projects. The topics and the project of the master thesis incorporate and condensate the main key features of selected initiatives as requested by the partner Latitudo 40, built on ReleafMi mockup v1.0 developed as part of Project Work 3 of AI4GOV Master Program, Urban GreenUp Project financed by European Commission and the municipality of Milan’s multiple strategies on reforestation and environmental improvements.
The first steps develop a documental review regarding the heat island effect, the current strategies, and goals of Milan’s municipality, as well as the European approaches toward climate crisis, the Latitudo 40 approach to the subject. Then a context analysis is developed, including the stakeholders’ map and problem reframing. This is followed by a step of envisioning the solutions and the subsequent idea development. The third step includes tool prototyping in its ML system core, AI incorporation, and back and front-end design of the tool. The last methodological step develops the final mockup of the tool, and a number of lessons learned.
Key lessons include the need to integrate data tools into existing government platforms, the application of artificial intelligence analysis to urban areas, and the importance of citizen engagement.
In conclusion, the development of this thesis provides a plausible solution to how data analytics and AI can play an outstanding role in solving the environmental challenges of contemporary cities. The suggested approach is even more remarkable considering that, although designed for the city of Milan, it is easily adaptable and reproducible for other cities in Europe and worldwide.
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