Scholarlink

Advanced HVAC control systems play a vital role in reducing energy use in commercial buildings, but ensuring indoor environmental quality (IEQ) remains essential. This paper presents a long-term, real-world evaluation of indoor climate conditions under AI-assisted HVAC control, using a commercially available and widely deployed control product. The study compares thermal comfort and indoor air quality in two actively used commercial buildings – an office and a shopping mall – before and after AI-assisted control implementation. Indoor conditions were assessed over one year using room-level sensor data and evaluated for compliance with EN 16798-1 and the Finnish Indoor Climate Classification (CIE), offering a practical benchmark rarely addressed in prior work. Results show that the AI-assisted control maintained or improved temperature and CO₂ levels relative to conventional systems, with some standard deviations attributed to occupant preferences rather than system performance. In the shopping mall, AI control achieved annual heating demand reductions of 42% and electricity savings of 22%. This study uniquely demonstrates the viability of a scaled commercial AI control system to reduce energy use while maintaining compliance with international indoor climate standards. It also underscores the value of using standardized metrics for evaluating IEQ under dynamic control strategies.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Data-Driven Assessment of Indoor Climate in Commercial Buildings Using AI-Assisted Control

  • 会议论文

  • 发表日期：

    2026年

查看全文
  • Tuule Mall Parts,
  • Hans Kristjan Aljas,
  • Ahmet Köse,
  • Juri Belikov,
  • Eduard Petlenkov

摘要

Advanced HVAC control systems play a vital role in reducing energy use in commercial buildings, but ensuring indoor environmental quality (IEQ) remains essential. This paper presents a long-term, real-world evaluation of indoor climate conditions under AI-assisted HVAC control, using a commercially available and widely deployed control product. The study compares thermal comfort and indoor air quality in two actively used commercial buildings – an office and a shopping mall – before and after AI-assisted control implementation. Indoor conditions were assessed over one year using room-level sensor data and evaluated for compliance with EN 16798-1 and the Finnish Indoor Climate Classification (CIE), offering a practical benchmark rarely addressed in prior work. Results show that the AI-assisted control maintained or improved temperature and CO₂ levels relative to conventional systems, with some standard deviations attributed to occupant preferences rather than system performance. In the shopping mall, AI control achieved annual heating demand reductions of 42% and electricity savings of 22%. This study uniquely demonstrates the viability of a scaled commercial AI control system to reduce energy use while maintaining compliance with international indoor climate standards. It also underscores the value of using standardized metrics for evaluating IEQ under dynamic control strategies.