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  • 标题:How IoT and Artificial Intelligence can improve energy efficiency in hospitals - a North Italian case study
  • 本地全文:下载
  • 作者:Riccardo Frassanito ; Tiziana Buso ; Stephanie Aumann
  • 期刊名称:E3S Web of Conferences
  • 印刷版ISSN:2267-1242
  • 电子版ISSN:2267-1242
  • 出版年度:2022
  • 卷号:343
  • 页码:1-11
  • DOI:10.1051/e3sconf/202234302001
  • 语种:English
  • 出版社:EDP Sciences
  • 摘要:Because of the COVID-19 pandemic, healthcare facilities have experienced pressure of increasing occupancy rates and more demanding Indoor Air Quality requirements in recent months. In this context, the efficient management of the HVAC system in these buildings has become a crucial topic to address. The retrofit project was the result of the joint effort of a digital solution provider, Enerbrain, and the Hospital’s energy services provider, Edison. By exploiting IoT and ICT technologies and cloud-based machine learning algorithms, the HVAC-related control features of the main heating and ventilation systems of the hospital have been upgraded with no major modifications to the existing setup. The implemented solution allows energy managers to remotely verify the real-time indoor comfort conditions and to control the upgraded systems, which, thanks to the machine learning adaptive algorithms, are now effectively meeting the required set-points through advanced optimization strategies. This paper presents the implementation of a retrofit measure applied to the HVAC Building Management System of a big public hospital in Lombardy and the energy savings achieved in the 2020-2021 heating season.
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