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English(EN) Software Engineering for AI-driven Building Operation

新论文详细介绍了人工智能在楼宇运营中的软件工程挑战

一篇新发表在arXiv上的论文讨论了人工智能驱动的楼宇运营特有的软件工程挑战。研究强调,与典型的数字环境不同,楼宇控制系统中的故障会产生不可逆转的物理后果,例如能源浪费或设备加速磨损。该论文指出了当前SE4AI实践中关键的缺失视角,并提出了在故障具有切实、持久影响的网络物理环境中工程化人工智能系统的最佳实践。 AI

影响 强调了人工智能在物理系统中的独特软件工程需求,可能影响网络物理应用的开发实践。

排序理由 该集群包含一篇发表在arXiv上的研究论文,详细介绍了人工智能应用的软件工程挑战。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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新论文详细介绍了人工智能在楼宇运营中的软件工程挑战

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该集群包含一篇发表在arXiv上的研究论文,详细介绍了人工智能应用的软件工程挑战。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Philipp Zech, Sascha Hammes, Johannes Weninger, J\"urgen Pannosch, Gernot Steidl ·

    面向AI驱动的建筑运营的软件工程

    arXiv:2608.16237v1 Announce Type: cross Abstract: Building operations are energy-inefficient. Artificial Intelligence (AI)-driven control systems promise benefits through optimization and predictive control, but deploying them in real buildings reveals a significant software engi…