INTELLIGENT ARCHITECTURES FOR SUSTAINABLE HOUSING: USE OF AI IN THE MANAGEMENT AND STORAGE OF RENEWABLE ENERGY

Abstract

The growing integration between digital technologies and renewable energy sources has redefined how energy consumption is organized in residential environments, especially in the context of sustainable housing. The present study aims to analyze how intelligent architectures based on artificial intelligence can optimize the management and storage of renewable energy in sustainable housing, aiming at greater energy efficiency and residential autonomy. Regarding the research design, a qualitative approach was adopted, guided by the interpretative analysis of data from multiple sources. This methodological choice allows for examining the investigated phenomenon in greater detail, considering not only the data itself but also the contexts in which they are embedded and the meanings associated with the analyzed technologies. By articulating theoretical and documentary information, it becomes possible to develop a consistent analysis capable of integrating different perspectives and expanding the understanding of the topic in a more comprehensive and contextualized manner. In summary, the research demonstrated that the integration of intelligent architectures, artificial intelligence, and energy storage systems contributes to the development of more efficient and autonomous housing by enabling more precise and adaptive energy management. The articulation of these technologies promotes the rational use of renewable sources and fosters greater balance in residential energy consumption, consolidating a housing model aligned with current demands for efficiency and sustainability.