Smart cities can be defined as scalable solutions that use ICT (Information and Communication Technologies) to improve the quality of life of citizens. To facilitate the transition to this scenario, it is necessary to propose a digitalization paradigm with different strategies, for example, reliable management systems to provide greater flexibility and resilience of buildings.
Currently, most tertiary buildings with high occupancy such as offices, universities, schools, primary health care centers, and shops are characterized by using manual systems, timers, or reactive rule-based systems. Therefore, buildings cannot anticipate future scenarios nor have the ability to adapt to unexpected events. Consequently, their energy-saving capacities are limited and considering that people spend 80-90% of their lives in indoor environments, it is important to improve their thermal comfort. In this context, it is necessary to develop technologies which improve both the energy efficiency of buildings and the well-being of their occupants. For this reason, the N2B2 project aims to implement a predictive control system, using an algorithm developed within the GRIC research group, which is based on the use of neural networks and historical operating data of the building.
Regarding to the socioeconomic and environmental impacts, the following can be highlighted:
- Incorporation of intelligent management to optimize the performance of building facilities .
- Maximizing the energy efficiency of heating and cooling systems.
- Improvement of user’s thermal comfort.
- Reduction of operational costs.
- Complies with the Sustainable Development Goals: SDG3 (Health and Well-being); SDG9 (Industry, Innovation, and Infrastructure); SDG11 (Sustainable Cities and Communities).