A novel framework for the assessment of indoor lighting solutions and its application for model learning spaces of a higher educational institution considering energy efficiency and human factors

Energy and Buildings, Journal Year: 2025, Volume and Issue: unknown, P. 115625 - 115625

Published: March 1, 2025

Language: Английский

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Using explainable artificial intelligence to predict sleep interruptions from indoor environmental conditions: an empirical study

Building Research & Information, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 20

Published: April 8, 2025

Language: Английский

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Influence of AC supply modes with different levels of energy sufficiency on cooling energy consumption in urban residential buildings

Energy and Buildings, Journal Year: 2025, Volume and Issue: unknown, P. 115789 - 115789

Published: April 1, 2025

Language: Английский

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Relationship Between Occupants’ Adaptive Behaviors, Air-Conditioning Usage, and Thermal Acceptability Among Residences in the Hot–Humid Climate of Indonesia

Buildings, Journal Year: 2024, Volume and Issue: 15(1), P. 73 - 73

Published: Dec. 29, 2024

A strategy for effectively utilizing occupants’ adaptive behaviors (OABs) to achieve thermal acceptability while maintaining low energy consumption is necessary. This study aims clarify the relationship between OABs and over various climate zones, as well change in due air conditioner (AC) ownership Indonesian residences. An online questionnaire consisting of perceived OABs’ time intensity, acceptability, personal attributes from 3000 respondents across Indonesia was analyzed using logistic regression. The results suggested that NV occupants engage more fan usage window opening enhance ventilative cooling, AC are likely adjust clothing use portable fans create cooler environments. Moreover, effects on residences varied depending local conditions. In hot climates, averages 90% intensity 92% complemented with active adjustment, were unable provide acceptability. These findings imply there a range indoor environmental conditions which conventional work well. highlights need promote behavioral adaptations, especially mixed-mode buildings, consider adaptations buildings based climates.

Language: Английский

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Data-Driven Ventilation and Energy Optimization in Smart Office Buildings: Insights from a High-Resolution Occupancy and Indoor Climate Dataset

Sustainability, Journal Year: 2024, Volume and Issue: 17(1), P. 58 - 58

Published: Dec. 25, 2024

This paper explores innovative approaches to reducing energy consumption in building ventilation systems through the implementation of adaptive control strategies. Using a publicly available high-resolution dataset spanning full year, study integrates real-time data on occupancy, CO2 levels, temperature, window state, and external environmental conditions. Notably, occupancy derived from computer vision-based detection using YOLOv5 algorithm provides an unprecedented level granularity. The evaluates five energy-saving strategies: Demand-Controlled Ventilation (DCV), occupancy-based control, time-based off-peak reduction, window-open temperature-based control. Among these, strategy achieved highest savings, power by 50%, while yielded significant 37.27% reduction. paper’s originality lies its holistic analysis multiple dynamic strategies, integrating diverse operational variables rarely combined prior research. findings highlight transformative potential advanced algorithms optimize HVAC performance. establishes new benchmark for energy-efficient management offering practical recommendations laying groundwork predictive models, renewable integration, occupant-centric systems.

Language: Английский

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Comparative study on the correlation between human local and overall thermal sensations based on supervised machine learning

Energy and Buildings, Journal Year: 2024, Volume and Issue: 328, P. 115061 - 115061

Published: Nov. 16, 2024

Language: Английский

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