Review
Construction & Building Technology
Haneul Choi, Chai Yoon Um, Kyungmo Kang, Hyungkeun Kim, Taeyeon Kim
Summary: This study conducted a comprehensive literature review on vision-based occupant information systems, proposing a five-tier taxonomy, presenting a systematic summary, reviewing the performance of sensing systems, analyzing the applicability of deep-learning techniques, summarizing privacy-preservation techniques, and providing control strategies and energy saving potential analysis. The analysis in this review contributes significantly towards addressing challenges in the research field.
BUILDING AND ENVIRONMENT
(2021)
Article
Construction & Building Technology
Haorui Wang, Junqi Wang, Zhuangbo Feng, Fariborz Haghighat, Shi-Jie Cao
Summary: Occupant-centric control of the environment is of great significance, especially in the context of epidemics, as it can contribute to prevention and energy saving. This study proposes an intelligent anti-infection ventilation strategy by combining computer vision with occupant-centric control, which dynamically maintains the infection risk around a target value and significantly saves ventilation energy consumption.
ENERGY AND BUILDINGS
(2023)
Article
Construction & Building Technology
Haneul Choi, Bonghoon Jeong, Joosang Lee, Hooseung Na, Kyungmo Kang, Taeyeon Kim
Summary: This study presents a method using deep learning and computer vision to estimate the real-time metabolic rate and clothing insulation of individuals. It also proposes a comfort temperature control strategy based on these characteristics, which has been successfully implemented and achieved satisfactory results.
BUILDING AND ENVIRONMENT
(2022)
Article
Thermodynamics
Jingsi Zhang, Xiang Zhou, Song Lei, Maohui Luo
Summary: The Personal Comfort System (PCS) aims to enhance thermal comfort satisfaction and reduce air conditioning energy consumption. Through experiments, simulations, and energy analysis, it has been shown that PCS can significantly improve occupants' thermal comfort and reduce energy consumption by 25%-40%.
BUILDING SIMULATION
(2022)
Article
Construction & Building Technology
Niels Lassen, Francesco Goia
Summary: This paper proposes a taxonomy for the classification of occupant-centric data streams, linking data sources to physiological and cognitive processes, helping to explain known gaps and challenges in predicting individual satisfaction with indoor climate conditions.
ENERGY AND BUILDINGS
(2021)
Article
Construction & Building Technology
Zu Wang, John Calautit, Paige Wenbin Tien, Shuangyu Wei, Wuxia Zhang, Yupeng Wu, Liang Xia
Summary: Occupant-Centric Control strategies have gained interest in adjusting building systems, but its application to natural ventilation systems and its impact on air quality have been overlooked. This study proposes an Occupant-Centric Heating and Natural Ventilation Control strategy that utilizes real-time occupant behavior data to improve thermal comfort, reduce energy consumption, and enhance indoor air quality. The strategy showed significant improvements in energy consumption, thermal comfort, and CO2 concentration compared to conventional control strategies.
ENERGY AND BUILDINGS
(2023)
Article
Construction & Building Technology
Maohui Luo, Qichun Zheng, Ye Zhao, Fei Zhao, Xiang Zhou
Summary: This study introduces the design and benefits of occupant-centric smart thermostats (OCST) in improving energy efficiency and thermal comfort. Through data analysis, it is shown that OCST can significantly reduce energy consumption in single-family houses.
ENERGY AND BUILDINGS
(2023)
Article
Energy & Fuels
Yue Lei, Sicheng Zhan, Eikichi Ono, Yuzhen Peng, Zhiang Zhang, Takamasa Hasama, Adrian Chong
Summary: This study proposes a practical deep reinforcement learning framework for occupant-centric control of HVAC systems, which considers personalized thermal comfort and occupant presence. The framework achieves multi-dimensional control of the HVAC system in a real environment and shows significant energy savings and improvements in comfort.
Article
Construction & Building Technology
Angela Sanguinetti, Sarah Outcault, Theresa Pistochini, Madison Hoffacker
Summary: This research explores the perception of teachers on indoor environmental quality (IEQ) in relation to actual monitored data. The findings indicate that teachers' perception of ventilation is not accurate, and those in classrooms with poorer ventilation were more satisfied with IEQ. Errors in HVAC system installation and programming contributed to misunderstandings. CO2 monitoring and teacher education are crucial for creating a safe classroom environment.
Article
Construction & Building Technology
Haneul Choi, HooSeung Na, Taehung Kim, Taeyeon Kim
Summary: Efforts have been made to estimate clothing insulation in real time, and a method based on deep learning-based vision recognition, named CloNet, showed high accuracy and practicality for building control. The study demonstrated that this vision-based estimation method is fast and effective, improving thermal preference and comfort vote in building control.
BUILDING AND ENVIRONMENT
(2021)
Article
Construction & Building Technology
Fanghui Cheng, Yuxin Wu, Shasha Gao, Chunhui Liao, Yong Cheng
Summary: This study comprehensively investigated subjective perceptions in a field environment chamber heated by stratum ventilation. Overall discomfort was related to the perception of being cooler than thermally neutral, with the head having the greatest influence on overall comfort followed by the feet. The dissatisfaction rate due to discomfort, mainly from cold feet, could exceed 10% if the feet sensation was lower than -0.5.
BUILDING AND ENVIRONMENT
(2022)
Article
Energy & Fuels
Veena Mathew, Ciji Pearl Kurian, Nevin Augustine
Summary: This work proposes a climate-responsive control method for switchable glazing using machine learning models. Experimental investigations are carried out on Polymer-dispersed liquid crystals (PDLCs) in a daylight artificial light integrated room to collect data for modeling. A support vector machine learning classification algorithm is designed to model the transparency change in PDLC. Real-time implementation of the model successfully predicts the states of switchable glazing under different climate conditions, and experimental verification is performed. The feasibility of PDLC in all window orientations is also simulated in this study.
Article
Construction & Building Technology
Canjun Li, Han Zhu, Xiangchao Lian, Yuxin Liu, Xiaohan Li, Yanbo Feng
Summary: To achieve occupant-centric building and control, it is important to consider occupant behavior characteristics and develop operational strategies accordingly. By studying the time-lag of shading behavior, an advanced prediction model was proposed, improving prediction accuracy. Furthermore, an operational logic that meets energy savings and comfort requirements was derived by describing the dynamic distribution of office room occupancy.
BUILDING AND ENVIRONMENT
(2022)
Article
Construction & Building Technology
Sudaporn Sudprasert
Summary: This study aimed to determine the effect of using evaporative air coolers indoors in the tropical climate of Thailand on thermal comfort, with results showing a lower thermal comfort level achieved by evaporative air coolers and potential discomfort from overly damp air. Air temperature and velocity were identified as the two most influential variables affecting thermal sensation in the application of evaporative air cooling.
BUILDING RESEARCH AND INFORMATION
(2021)
Article
Energy & Fuels
Han Li, Zheng Fu, Chang Xi, Nana Li, Wei Li, Xiangfei Kong
Summary: This study focused on the impact of parallel jet spacing (PJS) on the performance of multi-jet stratum ventilation. Through year-round multivariate analysis, it was found that PJS had different influences on indoor thermal comfort and energy utilization efficiency under different climatic conditions.
Article
Construction & Building Technology
Bin Zhou, Zhe Li, Bin Yang, Xiaojing Li, Faming Wang, Shen Wei
Summary: This study proposes a new integrated air supply strategy combining impinging jet ventilation (IJV) and intermittent airflow to enhance indoor thermal comfort. The results showed that the pulsating airflow created by the strategy could lower the mean air temperature above 0.6 m and raise it below 0.6 m. It also reduced overall and local thermal sensation, as well as the thermal sensation difference between the head and foot. The intermittent operation of IJV exhibited superior cooling performance without significantly affecting perceived air quality.
BUILDING AND ENVIRONMENT
(2023)
Review
Energy & Fuels
Bin Yang, Xin Zhu, Boan Wei, Minzhang Liu, Yifan Li, Zhihan Lv, Faming Wang
Summary: Heat dissipation in high-heat flux micro-devices is a pressing issue, and boiling heat transfer in microchannels is an effective method. A novel approach using image and machine learning techniques is proposed for flow pattern and heat transfer recognition. The support vector machine method successfully recognizes flow patterns based on texture characteristics. By combining image features with machine learning algorithms, the bubble dynamics behavior and flow pattern can be determined, revealing the mechanism of boiling heat transfer.
Article
Automation & Control Systems
Zhihao Wang, Dingde Jiang, Zhihan Lv
Summary: This article presents an AI-assisted trustworthy architecture based on dynamic heterogeneous redundancy (DHR) and deep reinforcement learning-based intelligent arbitration (DRLIA) algorithm to enhance security for industrial Internet of things (IIoT).
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Environmental Sciences
Yingying Zhao, Meng Su, Xin Meng, Jiying Liu, Faming Wang
Summary: This study evaluated the effects of environmental heat stress and personal cooling strategies on the physiological and perceptual responses of college students wearing personal protective equipment (PPE). The results showed that PPE can help mitigate heat stress, and the use of cooling systems can further reduce heat strain. The perceptual responses improved significantly with the use of personal cooling systems.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH
(2023)
Article
Computer Science, Cybernetics
Jinxia Wang, Stanislav Makowski, Alan Cieslik, Haibin Lv, Zhihan Lv
Summary: In the context of accelerated communication network technology, the emergence of virtual communities, virtual societies, metaverse, and other technologies has facilitated data access and sharing, but it has also led to the proliferation of fake news. This work focuses on detecting and identifying fake news in virtual communities, virtual societies, and metaverse. By reviewing the content and display methods of fake news, analyzing its impact and detection effect in various scenarios, and providing an intelligent outlook on detection and information security, this work offers theoretical references and new opportunities for addressing fake news in the virtual cyberspace.
IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS
(2023)
Article
Computer Science, Theory & Methods
Tongyue He, Junxin Chen, Ben-Guo He, Wei Wang, Zhi-Liang Zhu, Zhihan Lv
Summary: This article aims to explore the characteristics of sensors suitable for wearable devices and the relationship between data processing and applications. It fills the research gap by investigating fundamental data sources and the application of machine learning in sensor design and manufacturing, starting from different parts of the body as signal sources.
ACM COMPUTING SURVEYS
(2023)
Article
Computer Science, Artificial Intelligence
Weiping Liu, Xiaozhen Lin, Xinghong Chen, Qing Wang, Xiumei Wang, Bin Yang, Naiqing Cai, Rong Chen, Guannan Chen, Yu Lin
Summary: This study proposed a novel model, GTSN, to estimate the MDS-UPDRS score of PD tremors based on video analysis. The results demonstrated the effectiveness of computer-assisted assessment for PD tremors.
MEDICAL IMAGE ANALYSIS
(2023)
Article
Engineering, Environmental
Chan Lu, Wenhui Yang, Faming Wang, Bin Li, Zijing Liu, Hongsen Liao
Summary: The study found that exposure to pollutants during pregnancy and after birth has an impact on children's doctor diagnosed pneumonia (DDP). Intrauterine and post-natal exposure to PM2.5, PM2.5-10, and PM10 were associated with DDP. Intrauterine exposure to PM2.5 and post-natal exposure to PM10 were associated with increased risk of pneumonia. The second trimester, third trimester, and first year after birth were identified as critical windows for PM2.5, PM2.5-10, and PM10 exposure. Daytime exposure to traffic-related pollution, especially in early life, increased the risk of DDP.
JOURNAL OF HAZARDOUS MATERIALS
(2023)
Article
Engineering, Environmental
Chan Lu, Qin Li, Zipeng Qiao, Qin Liu, Faming Wang
Summary: This study found that air pollutants, especially PM2.5 during the middle of gestation and PM10 during the early post-natal period, played a crucial role in the onset and recurrent attacks of otitis media (OM) in kindergarten children. Certain time windows, such as the 2nd trimester in utero and the post-natal period, were particularly important for the association between air pollution and OM.
JOURNAL OF HAZARDOUS MATERIALS
(2023)
Article
Engineering, Mechanical
Siyuan Sun, Bin Yang, Qilin Zhang, Roland Wuechner, Licheng Pan, Haitao Zhu
Summary: This paper aims to develop a fast online implementation of covariance-driven SSI (COV-SSI), which analyzes the computational cost of COV-SSI and accelerates two time-consuming steps. Numerical examples are used to validate the speed and accuracy of the proposed fast online strategies.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2023)
Article
Multidisciplinary Sciences
Zhihan Lv, Chen Cheng, Haibin Lv
Summary: This study aims to improve the efficiency of automatic identification of pavement distress and address the challenges in identifying and detecting pavement distress. It analyzes the identification method and types of pavement distress, describes the design concept of deep learning in pavement distress recognition, and applies the Mask R-CNN model in road crack distress recognition. The results show high accuracy in the model's recognition performance and different crack detection methods, providing valuable insights for the application of deep CNNs in pavement distress recognition and contributing to the improvement of road traffic conditions for smart cities in the future.
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES
(2023)
Article
Construction & Building Technology
Yanpeng Wu, Xiaoyu Li, Qiaoyang Zhong, Faming Wang, Bin Yang
Summary: This study created a PVDF/SiO2/Ag composite nanofiber membrane with superhydrophobic and antibacterial properties using an electrospinning method. The membrane was deposited on PET fibers to create an air filter material. The results showed that the addition of nano-silver significantly improved the antibacterial performance while increasing the concentration of hydrophobic nano-SiO2 improved the hydrophobicity. The composite nanofiber membrane had a filtration efficiency of 99.94% for 0.3μm particulate matter and a drag pressure drop of 112.3 Pa, with a filtration efficiency for air microorganisms greater than 99.99%.
JOURNAL OF BUILDING ENGINEERING
(2023)
Article
Computer Science, Cybernetics
Zhihan Lv, Chen Cheng, Antonio Guerrieri, Giancarlo Fortino
Summary: More data are generated through mobile network technology, giving birth to the cyber-physical social intelligent ecosystem (C & P-SIE). This survey studies the development of physical social intelligence, discussing its applications in various domains such as intelligent transportation, healthcare, public service, economy, and social networking. It also explores the future prospects of behavior modeling in C & P-SIE under information security, data-driven techniques, and cooperative artificial intelligence technologies. This research provides a theoretical foundation and new opportunities for the digital and intelligent development of smart cities and social systems.
IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS
(2023)
Proceedings Paper
Computer Science, Artificial Intelligence
Bin Cao, Xingyi Yang, Ziming Li, Yunjian Fu, Zhihan Lv
Summary: This paper proposes a color image compression method based on Tucker decomposition and multi-objective optimization. The color image is regarded as a third-order tensor, and the method compresses the image by decomposing and optimizing the tensor. The evaluation methods for image compression quality include tensor size compression ratio and Hu invariant moment similarity. In addition, a five-objective optimization model is constructed, which considers multiple aspects of image compression. Experimental results show that the proposed method effectively solves the problem of color image compression.
2023 8TH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING AND BIG DATA ANALYTICS, ICCCBDA
(2023)
Article
Clinical Neurology
Xun Han, Dongjun Wan, Shuhua Zhang, Ziming Yin, Siyang Huang, Fengbo Xie, Junhong Guo, Hongli Qu, Yuanrong Yao, Huifang Xu, Dongfang Li, Sufen Chen, Faming Wang, Hebo Wang, Chunfu Chen, Qiu He, Ming Dong, Qi Wan, Yanmei Xu, Min Chen, Fanhong Yan, Xiaolin Wang, Rongfei Wang, Mingjie Zhang, Ye Ran, Zhihua Jia, Yinglu Liu, Xiaoyan Chen, Lei Hou, Dengfa Zhao, Zhao Dong, Shengyuan Yu
Summary: CDSS 2.0 was developed to diagnose headache disorders by acquiring clinical information through human-computer conversations. The system achieved high diagnostic accuracy and was well accepted by patients.
JOURNAL OF HEADACHE AND PAIN
(2023)
Article
Construction & Building Technology
Parth Bansal, Steven Jige Quan
Summary: This study investigates the relationship between urban form and canopy layer urban heat island (CUHI) using a relatively large sample of microclimate sensors in Seoul, Korea. The study compares different statistical models and finds that the spatially explicit gradient boosting decision tree (GBDT) model has the highest accuracy. The study also shows that the effect of urban form on CUHI varies at different time instances during the day. These findings provide valuable insights for planners to understand the complexity of urban climate and reduce CUHI magnitude.
BUILDING AND ENVIRONMENT
(2024)
Article
Construction & Building Technology
Miaomiao Liu, Salah Almazmumi, Pinlu Cao, Carlos Jimenez-bescos, John Kaiser Calautit
Summary: Windcatchers provide effective low-energy ventilation and summer passive cooling in temperate climates. However, their use in winter is limited due to significant ventilation heat loss and potential discomfort. This study evaluates the applicability of windcatchers in low-temperature conditions, highlighting the need for control strategies to reduce over-ventilation and the integration of heat recovery or thermal storage to enhance winter thermal conditions.
BUILDING AND ENVIRONMENT
(2024)
Review
Construction & Building Technology
Behrouz Nourozi, Aneta Wierzbicka, Runming Yao, Sasan Sadrizadeh
Summary: This article presents a systematic review of ventilation solutions in hospital wards, aiming to enhance pathogen removal performance while maintaining patient and healthcare staff comfort using air-cleaning techniques. The study reveals the importance of proper ventilation systems in reducing infection risk and adverse effects of cross-contamination.
BUILDING AND ENVIRONMENT
(2024)
Article
Construction & Building Technology
Zhen Yang, Weirong Zhang, Hongkai Liu, Weijia Zhang, Mingyuan Qin
Summary: The study examines the influence of personalized local heating on the thermal comfort of occupants in old residential buildings. The findings reveal that personalized local heating can increase the overall thermal sensation of occupants, but only a few methods are effective in enhancing thermal comfort. The chosen heating methods and background temperature affect the participants' selection of heating parts.
BUILDING AND ENVIRONMENT
(2024)
Article
Construction & Building Technology
Hong Cheng, Dan Norback, Huilin Zhang, Liu Yang, Baizhan Li, Yinping Zhang, Zhuohui Zhao, Qihong Deng, Chen Huang, Xu Yang, Chan Lu, Hua Qian, Tingting Wang, Ling Zhang, Wei Yu, Juan Wang, Xin Zhang
Summary: The home environment and sick building syndrome (SBS) symptoms in five southern Chinese cities have been studied over time. The study found a decrease in asthma prevalence and an increase in allergic rhinitis. Cockroaches, rats, mice, mosquitoes or flies were identified as consistent biological risk factors for SBS symptoms, while redecoration, buying new furniture, and traffic air pollution were identified as other risk factors.
BUILDING AND ENVIRONMENT
(2024)
Article
Construction & Building Technology
Chaojie Xing, Zhengtao Ai, Zhiwei Liu, Cheuk Ming Mak, Hai Ming Wong
Summary: This study experimentally investigated the emission characteristics of droplets around the mouth during dental treatments. The results showed that the peak mass fraction of droplets occurs within the size range of 20 μm to 100 μm, and droplets with a diameter less than 200 μm account for over 80% of the mass fraction. The dominant emission direction of droplets is towards the dummy's head and chest, forming an approximately cone shape.
BUILDING AND ENVIRONMENT
(2024)
Article
Construction & Building Technology
Zhijian Liu, Zhe Han, Lina Hu, Chenxing Hu, Rui Rong
Summary: This study compared the effects of different respiratory behaviors on the distribution of aerosols in a ward and the risk of infection for healthcare workers using numerical simulation. It was found that talking in the ward significantly increased aerosol concentrations, particularly short periods of talking. Wards designed with side-supply ventilation had lower overall infection risk. Talking alternately between healthcare workers and patients slightly extended the impact time of aerosols.
BUILDING AND ENVIRONMENT
(2024)
Article
Construction & Building Technology
Yan Yan, Mengyuan Kang, Haodong Zhang, Zhiwei Lian, Xiaojun Fan, Chandra Sekhar, Pawel Wargocki, Li Lan
Summary: In a high-density city, opening windows for sleep may lead to increased indoor temperature, higher PM2.5 concentration, and noise disturbance, which can negatively impact sleep quality.
BUILDING AND ENVIRONMENT
(2024)
Article
Construction & Building Technology
Yan Bai, Liang Liu, Kai Liu, Shuai Yu, Yifan Shen, Di Sun
Summary: This study developed a non-intrusive personal thermal comfort model using machine learning techniques combined with infrared facial recognition. The results showed that the ensemble learning models perform better than traditional models, and the broad learning model has a higher prediction precision with lower computational complexity and faster training speed compared to deep neural networks. The findings provide a reference for optimizing building thermal environments.
BUILDING AND ENVIRONMENT
(2024)
Article
Construction & Building Technology
Yue Lei, Zeynep Duygu Tekler, Sicheng Zhan, Clayton Miller, Adrian Chong
Summary: Mixed-mode ventilation is a promising solution for achieving energy-efficient and comfortable indoor environments. This study found that occupants can thermally adapt when switching between natural ventilation (NV) and air-conditioning (AC) modes within the same day, with the adaptation process stabilizing between 35 to 45 minutes after the mode switch. These findings are important for optimizing thermal comfort in mixed-mode controls, considering the dynamic nature of thermal adaptation.
BUILDING AND ENVIRONMENT
(2024)
Article
Construction & Building Technology
Nan Mo, Jie Han, Yingde Yin, Yelin Zhang
Summary: This study develops a method based on the LCZ framework for a comprehensive evaluation of urban-scale heat island effects, considering the impact of geographic factors on LST. The results show that Guilin's geomorphological conditions lead to abnormal heat island effects during winter, and the cooling effects of mountains and water bodies vary seasonally in different built areas, with LCZ 2 exhibiting the strongest cooling effect.
BUILDING AND ENVIRONMENT
(2024)
Article
Construction & Building Technology
Tunga Salthammer
Summary: Monitoring the potential formaldehyde emission of wood-based materials through test chamber investigations has significantly contributed to reducing indoor formaldehyde concentrations. However, the different methodologies used in these procedures prevent direct result comparison. Empirical models for converting formaldehyde steady-state concentrations based on temperature, humidity, air change rate, and loading were developed in the 1970s and have been modified to accommodate the development of lower-emitting materials. Formaldehyde emissions from wood-based materials are complex and require nonlinear regression tools for mathematical analysis.
BUILDING AND ENVIRONMENT
(2024)
Article
Construction & Building Technology
Katarina Stebelova, Katarina Kovacova, Zuzana Dzirbikova, Peter Hanuliak, Tomas Bacigal, Peter Hartman, Andrea Vargova, Jozef Hraska
Summary: This study investigated the impact of reduced short-wavelength light on the hormone melatonin metabolite 6-sulfatoxymelatonin (u-sMEL) and examined the association between previous day's light exposure and u-sMEL. It was found that reducing short-wavelength light during the day did not change the concentration of u-sMEL. Personal photopic illuminance was positively correlated with u-sMEL in the reference week. The illuminance had a significant impact on u-sMEL, as shown by the evaluation of the mean of all three urine samples. However, this correlation was not found in the experimental week.
BUILDING AND ENVIRONMENT
(2024)
Article
Construction & Building Technology
Ruoxin Xiong, Ying Shi, Haoming Jing, Wei Liang, Yorie Nakahira, Pingbo Tang
Summary: This study proposes a data-model integration method to identify and calibrate uncertainties in machine learning models, leading to improved thermal perception predictions. The method utilizes the Multidimensional Association Rule Mining algorithm to identify biased human responses and enhances prediction accuracy and reliability. The study also evaluates different calibration techniques and discovers their potential in enhancing prediction reliability.
BUILDING AND ENVIRONMENT
(2024)
Article
Construction & Building Technology
Beichao Hu, Zeda Yin, Abderrachid Hamrani, Arturo Leon, Dwayne McDaniel
Summary: This paper introduces an innovative super-resolution approach to model the air flow and temperature field in the cold aisle of a data center. The proposed method reconstructs a high-fidelity flow field by using a low-fidelity flow field, significantly reducing the computational time and enabling real-time prediction.
BUILDING AND ENVIRONMENT
(2024)