InovaCID project summary and context

The InovaCID research project develops innovative applications for smart cities using machine learning algorithms. Three use cases are the focus of the InovaCID project:

• Use Case 1 - ML in healthcare smart city projects

• Use Case 2 - Innovation in architecture for the urban development in smart city projects

• Use Case 3 - Energy efficiency and sustainability in smart cities with machine learning

Use case 1 proposes to research the application of machine learning algorithms in the context of healthcare for a smart city. As a proof of concept, it develops an intelligent application that investigates infectious diseases' occurrence and possible impacts in a given city or region. The research aims to solve an essential problem of smart cities: decision-making in the health area and supporting the planning and governance of cities.

In relation to the UN's sustainable development goals (SDGs), use case 1 falls under SDG 3 (Good Health and Wellbeing) as the research aims to contribute to solving an important problem in smart cities: decision-making in the health area supporting city planning and governance.

Use case 2 aims to investigate and propose innovative architecture and urban development solutions. The use case evaluates the impact of new architectural solutions for urban development in a smart city context. This use case fits into SDG 11 (Sustainable Cities and Communities) as it promotes a more inclusive and sustainable urban environment in cities.

Use case 3 proposes researching and developing a reinforcement learning algorithm or equivalent technology to optimize energy efficiency. This is an important and decisive aspect of a smart city project, where energy savings and diversity of the energy matrix aimed at sustainability are important elements.

Use case 3 fits into SDG 7 (Affordable and Clean Energy) as it promotes optimizing the use of network resources, which improves energy efficiency and reduces the carbon footprint.