Challenges and opportunities of occupant-centric building controls in real-world implementation: A critical review

Energy and Buildings, Год журнала: 2024, Номер 308, С. 113958 - 113958

Опубликована: Фев. 14, 2024

Over the past few decades, attention in buildings’ design and operation has gradually shifted from promoting only energy efficiency objectives to also addressing human comfort well-being. Researchers have developed a wide range of control algorithms ranging rule-based controls complex learning approaches that can fully capture occupants’ personalized preferences smart buildings. This direction occupant-centric building bridge gap between satisfaction sustainability objectives. However, most these promising technologies not yet found their way into real-world applications. study will perform critical review on thermal lighting studies aiming (i) analyze strengths weaknesses different approaches; (ii) identify requirements for techniques be implemented systems; (iii) propose new research directions promote usability such catalyst towards adoption. Computational complexity, integration with Building Automation Systems (BAS), data availability quality, scalability, lack more featuring actual implementation emerge as barriers. Addressing challenges is imperative successful deployment

Язык: Английский

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Human physiology for personal thermal comfort-based HVAC control – A review

Building and Environment, Год журнала: 2023, Номер 240, С. 110418 - 110418

Опубликована: Май 22, 2023

Standardized methods for thermal comfort assessment already exist, namely the predicted mean vote (PMV) and adaptive model, both valid groups of people. To identify whether a specific person is comfortable under different factors such as thermal, air quality, lighting, acoustics, only current reliable method subjective evaluation. reduce need occupant feedback, personal models are currently being developed that aim to predict response based on information from its surroundings. These leverage machine learning tools have been found provide suitable estimations responses. According literature, an average prediction accuracy 70–80% attainable. Therefore, these promoted innovative efficient ways comfort-based HVAC control. The challenge however identifying most relevant indicators acquiring them in simple way. Integrating anthropometric data, e.g., age, sex, body mass index may represent generating model. Including physiological data skin temperature, heart rate, signal transformation could increase performance. Strong relationships were identified between indicators, their variation was not be governed solely by thermoregulation. Few automatic control implementation examples using shows challenges still exist. In order achieve accurate control, certain issues remain regarding acceptable thresholds model performance optimum set combination it.

Язык: Английский

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Personal comfort models based on a 6‐month experiment using environmental parameters and data from wearables

Indoor Air, Год журнала: 2022, Номер 32(11)

Опубликована: Ноя. 1, 2022

Personal thermal comfort models are a paradigm shift in predicting how building occupants perceive their environment. Previous work has critical limitations related to the length of data collected and diversity spaces. This paper outlines longitudinal field study comprising 20 participants who answered Right-Here-Right-Now surveys using smartwatch for 180 days. We more than 1080 field-based per participant. Surveys were matched with environmental physiological measured variables indoors homes offices. then trained tested seven machine learning participant predict preferences. Participants indicated 58% time want no change environment despite completing 75% these at temperatures higher 26.6°C. All but one personal model had median prediction accuracy 0.78 (F1-score). Skin, indoor, near body temperatures, heart rate most valuable accurate prediction. found that ≈250–300 points needed We, however, identified strategies significantly reduce this number. Our provides quantitative evidence on improve models, prove benefits wearable devices preference, validate results from previous studies.

Язык: Английский

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Cohort comfort models — Using occupant’s similarity to predict personal thermal preference with less data

Building and Environment, Год журнала: 2022, Номер 227, С. 109685 - 109685

Опубликована: Окт. 13, 2022

Язык: Английский

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Cozie Apple: An iOS mobile and smartwatch application for environmental quality satisfaction and physiological data collection

Journal of Physics Conference Series, Год журнала: 2023, Номер 2600(14), С. 142003 - 142003

Опубликована: Ноя. 1, 2023

Abstract Collecting feedback from people in indoor and outdoor environments is traditionally challenging complex to achieve a reliable, longitudinal, non-intrusive way. This paper introduces Cozie Apple, an open-source mobile smartwatch application for iOS devices. platform allows complete watch-based micro-survey provide real-time about environmental conditions via their Apple Watch. It leverages the inbuilt sensors of collect physiological (e.g., heart rate, activity) (sound level) data. outlines data collected 48 research participants who used report perceptions urban-scale comfort (noise thermal) contextual factors such as they were with what activity doing. The results 2,400 micro-surveys across various urban settings are illustrated this paper, showing variability noise-related distractions, thermal comfort, associated context. show that experienced at least little noise distraction 58% time, talking being most common reason (46%). effort novel due its focus on spatial temporal scalability collection noise, distraction, information. These set stage larger deployments, deeper analysis, more helpful prediction models toward better understanding occupants’ needs perceptions. innovations could result control signals building systems or nudges change behavior.

Язык: Английский

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A data-driven agent-based model of occupants’ thermal comfort behaviors for the planning of district-scale flexible work arrangements

Building and Environment, Год журнала: 2024, Номер 257, С. 111479 - 111479

Опубликована: Апрель 9, 2024

In a global context of increasing flexibility in the way workplaces and districts which they are located used, there is need for occupant-driven approaches to plan urban energy systems. Several authors have suggested use agent-based models (ABM) building occupants simulations due their ability reproduce emergent behaviors from individual agents' actions. However, few works literature take full advantage ABM paradigm, accounting both occupant presence energy-relevant at district scale. this work, we propose methodology develop data-driven, model occupants' activities thermal comfort an district. Our combines campus-scale Wi-Fi data derive feasible activity location plans, along with preference profiles derived longitudinal field study where off-the-shelf, non-intrusive sensors were used capture right-here-right-now 35 participants same case then explore how different operation strategies could affect performance increased workspace flexibility. results show that by providing diversity conditions, buildings having set point temperatures, hours be improved average about 10% little effect on performance. Meanwhile, 6%–15% decrease space cooling intensity was observed when implementing ventilation setpoint controls, regardless choice scenario.

Язык: Английский

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Non-Intrusive Infrared Facial Thermography for Personal Thermal Sensation Prediction Models: A Field Study

Building and Environment, Год журнала: 2025, Номер unknown, С. 112606 - 112606

Опубликована: Янв. 1, 2025

Язык: Английский

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Evaluating compliance with HeatSuite for monitoring in situ physiological and perceptual responses and personal environmental exposure

npj Digital Medicine, Год журнала: 2025, Номер 8(1)

Опубликована: Апрель 24, 2025

Язык: Английский

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Enhancing thermal comfort prediction in high-speed trains through machine learning and physiological signals integration

Journal of Thermal Biology, Год журнала: 2024, Номер 121, С. 103828 - 103828

Опубликована: Март 27, 2024

Язык: Английский

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Causal thinking: Uncovering hidden assumptions and interpretations of statistical analysis in building science

Building and Environment, Год журнала: 2024, Номер 259, С. 111530 - 111530

Опубликована: Апрель 16, 2024

Causal thinking emphasizes the understanding of asymmetric causal relationships between variables, requiring us to specify which variable is cause (independent variable) and effect (dependent variable). Reversing relationship direction can lead profoundly different assumptions interpretations. We demonstrate this by comparing two linear regression methods used in thermal comfort data analysis: Approach (a), regresses sensation votes (y-axis) on indoor temperature (x-axis), (b), does reverse, regressing (x-axis). From a correlational perspective, approaches may appear interchangeable, but reveals substantial practically significant differences them. (a) aligns with most laboratory studies considers occupants' sensations as responses temperature. In contrast, rooted adaptive theory, suggests that trigger behavioral changes, turn alter Using same data, we found (b) leads what call 'preferred zone', 10 °C narrower than conventionally derived zone using (a). The zone' might be interpreted conditions occupants are likely choose when they have control over their personal environmental settings. This finding has important implications for occupant building energy efficiency. highlight importance integrating into correlation-based statistical methods, been prevalent science research, especially given increasing volume built environment.

Язык: Английский

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