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New paper details software engineering challenges for AI in building operations

By PulseAugur Editorial · [1 sources] ·

A new paper published on arXiv addresses the software engineering challenges specific to AI-driven building operations. The research highlights that unlike typical digital environments, failures in building control systems have irreversible physical consequences, such as wasted energy or accelerated equipment wear. The paper identifies key missing perspectives in current SE4AI practices and proposes best practices for engineering AI systems in cyber-physical contexts where failures have tangible, lasting impacts. AI

IMPACT Highlights unique software engineering needs for AI in physical systems, potentially influencing development practices for cyber-physical applications.

RANK_REASON The cluster contains a research paper published on arXiv detailing software engineering challenges for AI applications. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New paper details software engineering challenges for AI in building operations

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The cluster contains a research paper published on arXiv detailing software engineering challenges for AI applications. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

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

    Software Engineering for AI-driven Building Operation

    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…

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