Research on Intelligent Automation Control Strategies for Reducing Building Energy Consumption and Carbon Emissions
Rongdong Chen
European Journal of AI, Computing & Informatics, 2026, vol. 2, issue 2, 139-152
Abstract:
This research investigates intelligent automation control strategies aimed at reducing building energy consumption and carbon emissions. By integrating advanced control algorithms, sensor technologies, and data-driven optimization techniques, the study explores innovative solutions to enhance energy efficiency in buildings. A comprehensive methodology is employed, encompassing system modeling, experimental validation, and performance analysis. Results demonstrate significant potential for intelligent automation to minimize energy usage and emissions while maintaining occupant comfort. The findings provide actionable insights for sustainable building management and contribute to global efforts in mitigating climate change.
Keywords: intelligent automation; energy efficiency; carbon emissions; building control strategies; sustainable buildings (search for similar items in EconPapers)
Date: 2026
References: Add references at CitEc
Citations:
Downloads: (external link)
https://pinnaclepubs.com/index.php/EJACI/article/view/778/746 (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:dba:ejacia:v:2:y:2026:i:2:p:139-152
Access Statistics for this article
More articles in European Journal of AI, Computing & Informatics from Pinnacle Academic Press
Bibliographic data for series maintained by Joseph Clark ().