面向绿色医院设计与运营的智能能源管理研究进展

IF 5.3 2区 计算机科学 Q2 ROBOTICS
IEEE Robotics and Automation Letters Pub Date : 2026-07-01 Epub Date: 2026-06-08 DOI:10.1109/LRA.2026.3701567
Qing Wang;Leqi Weng;Taojun Wang;Jingshan Li
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引用次数: 0

摘要

在医院和卫生保健设施中减少能源消耗和采用替代能源或可再生能源对于可持续发展、节能和卫生保健相关的减排具有重要意义。因此,绿色医院已被引入作为医疗保健的范式转变。本文从能效提高、替代或可再生能源整合、可持续建筑设计和绿色物流等方面,特别是优化和人工智能(AI)应用等方面,综述了绿色医院设计和运营中智能能源管理的最新进展。本文总结了代表性方法和实际案例,以展示优化模型、数据驱动方法和人工智能技术如何支持医疗机构的节能、运营弹性和碳足迹减少。还讨论了主要挑战,包括数据质量、系统互操作性、模型可解释性、网络安全和政策支持。本文简要概述了可持续和人工智能绿色医院的最新进展和潜在研究方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Recent Advances in Intelligent Energy Management for Design and Operation of Green Hospitals
Reducing energy consumption and adopting alternative or renewable energy in hospitals and healthcare facilities are of significant importance for sustainable development, energy savings, and healthcare-related emission reduction. Thus, green hospitals have been introduced as a paradigm shift in healthcare. In this paper, a review of recent advances in intelligent energy management for the design and operation of green hospitals is presented from the perspectives of energy efficiency improvement, alternative or renewable energy integration, sustainable building design, and green logistics, particularly in terms of optimization and artificial intelligence (AI) applications. Representative methods and practical cases are summarized to show how optimization models, data-driven approaches, and AI technologies can support energy savings, operational resilience, and carbon footprint reduction in healthcare facilities. Major challenges are also discussed, including data quality, system interoperability, model interpretability, cybersecurity, and policy support. This review provides a concise overview of recent progress and potential research directions for sustainable and AI-enabled green hospitals.
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来源期刊
IEEE Robotics and Automation Letters
IEEE Robotics and Automation Letters Computer Science-Computer Science Applications
CiteScore
9.60
自引率
15.40%
发文量
1428
期刊介绍: The scope of this journal is to publish peer-reviewed articles that provide a timely and concise account of innovative research ideas and application results, reporting significant theoretical findings and application case studies in areas of robotics and automation.
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